Developing IMU Sensors For Capturing Motion In Sports

IMU sensors are pretty useful because when strapped to the right location and given the right context they can provide very insightful information about an athlete’s (or anyone’s) movements. In this post, we are going to look at a couple of options in the market that allows us to skip the hardware development and jump right into the application development. Feel free to skip to the different sections that interest you:

[ Intro To IMUsmbientlabsNotch SensorNotch Mocap TestCustom Sensors]

Intro To IMUs

In case this is the first time you are hearing about IMU, here’s a brief intro. IMU stands for Inertial Measurement Unit; it is an electronic device that typically has accelerometers, gyroscopes and magnetometers, and it measures its own acceleration, angular rate (or spin rate) and surrounding magnetic field. IMUs are not only used in sports, in fact, it is used in many consumer electronic devices. Our smartphones for one has IMUs for detecting the orientation of the phone and changing the display to portrait or landscape. The IMUs also allows for functions such as undoing texting errors, a spirit level and motion sensor games. If a user carries the phone with them in their pockets most of their waking hours, it can act as a pedometer counting steps and detect when the user is sedentary. For runners who use running apps to track their runs, IMUs enable some apps to track indoor runs and cadence. Sports Engineering Researchers have used smartphones for tracking wheelchair rugby activities and classifying different sporting activities.

As great as the smartphones are with inbuilt IMU, GPS and processing power to give us real-time analysis, we don’t really want to strap an expensive smartphone onto a football player’s calf to monitor their kicking or tape an iPhone to a tennis racket to measure swing metrics. That’s why companies like Qlipp has developed sensors for tennis or Zepp which has sensors for a number of bat-and-ball or swing type sports. Then there are sensors for rowing, running, surfing, mountain biking and more. There are also different sports equipment that has in-built IMU sensors. Like smart balls (basketball, football, cricket ball etc), smart shoes, smart helmets, smart rackets etc, it could go on and on.

But sometimes we might still not find a sensor product on the market that is right for our sports or health application. So we explore the option of developing something on our own. Fortunately, we don’t necessarily have to start from scratch* because these days there are generic IMU sensor platforms that are designed and built for people who want to develop a sensor for a custom application. They often have the standard 9-DOF (degree of freedom) sensor setup and come with software SDK that allows developers to build their own applications for processing and analysing the data. Let’s look at a couple of options below.

[*when I say scratch, I mean getting sensor boards from SparkFun, Adafruit, Seeedstudio, Tindie etc]

mbientlab

mbientlab successfully launched their first Bluetooth IMU sensor on Kickstarter. They pitched it as a development and production platform for wearables with simple API for iOS and Android. There was some simple soldering required when people bought the first product. I didn’t get one from that campaign but I did get a later updated version which they called MetawearRG. What impressed me when I first got it was the size of it – it’s small and compact and I could use it to build/redesign a smart basketball prototype for a client. Then when I started testing it, I found that their API was really easy to use and I could use their sample iOS app to build a custom app for testing within a (reasonably) short time.

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Smart Basketball Prototype and Watch app for tracking optimal shots

Since then, they have made many other versions of sensors with:

  • slightly different sensor configurations,
  • options of coin cell or rechargeable lithium battery,
  • accessories such as cases, clips or wristbands,
  • sensor fusion firmware,
  • cloud services, and
  • hubs to manage multiple sensors.
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Metawear RG with custom 3d printed sleeve/case (L) and Metamotion (R)

I haven’t had the chance to try everything but I have to say, I have had a good experience using their Metawear and Metamotion sensors to build various proof of concepts and I am still using them for a number of projects. The sensor data can be streamed to your smartphone or logged on the device. In terms of API support, on top of iOS and Android, they have added Python, C, C# and Javascript, so developers can build stuff on various platforms.

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Sample/Template Metawear iOS app for testing

Looking at their new website revamp and some recent emails they sent out about new platform developments, they seem to be putting more focus into the allied health space, in particular, measuring range-of-motion (ROM). They are currently beta testing an app called the MetaClinic and it looks like they are using skeleton-tracking the likes of motion capture systems which would probably mean we need to use multiple sensors. That should be interesting.

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MetaClinic App by mbientlab

Notch Sensors

Notch also launched on kickstarter, in fact slightly earlier than mbientlabs’ campaign. They had an interesting concept of integrating individual IMUs into custom designed clothing using pockets in discreet locations. Unfortunately, they weren’t successful at that instance. Their initial use case probably wasn’t strong enough. So I guess the founders went back to the drawing board, revamped it all and went with the “motion capture” approach for developers.

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Notch sensor with elastic band and clip

With the new design, the shape of the IMU sensor is essentially the same but they have ditched the micro-usb in each IMU for contact pins and made it water-resistant (IP67). They also designed elastic bands of varying lengths with a sensor clip and a user can secure each sensor up to 15 different locations on their body including head, chest, upper arms, wrists, hands, waist, thighs, ankles and feet. So instead of selling individual IMUs, they sell a kit of 6 IMUs with a set of elastic bands, and if a user wants to do a full (body) setup, they will need 3 kits.

IMG_1130

The Pioneer Kit: 6 IMUs with charging case and elastic bands with clips.

A quick test and review (for biomechanics)

I had the opportunity to run a short pilot test with one (the pioneer) kit in a biomechanics lab. I used the lower body setup which used all 6 IMUs strapped on my chest, waist, thighs and shins/ankles. In terms of setting up, it was pretty straightforward. After following an initial calibration procedure of all the IMUs in the case, I put on the bands and clipped each IMU to the right location according to the different colours as indicated on the app. The only thing is putting on the bands takes a bit of practice and I had to swing around to check that the bands are not too tight and restricting movement. Even though I don’t have muscly quads, I felt that the bands were somewhat tight and needed adjusting after a while.

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Setting up the Notch IMUs for lower body measurements

For testing, I did a simple protocol of walking, stopping and doing 3 squats of varying depths. Then I compared my knee angles measured on the notch and the motion capture system. A few quick things that I took out of the knee angle measurements were:

  • The angle measured by Notch is the exterior angle while the motion capture system looks at the interior angle. So it needs a quick recalculation before comparison.
  • Assuming the motion capture system is the more accurate measurement, Notch had a larger error as squats went deeper.
  • But for walking, the knee angles measured were quite close.

It’s wasn’t a very elaborate test but even from this simple outcome, I can safely say it’s probably not the best tool for accurate joint angle measurements. Although for a quick 3D visual feedback on movements, it might work. Here’s the clip of me doing the test described above (feel free to rotate the video to get different perspectives):



Further to that, I could only download angle data. If I wanted the raw sensor (acceleration and gyro) data, I would need to pay for an extended license that is renewed annually.

In terms of custom development support, they used to have support for iOS but they seem to have taken that off now and only have support for Android which I thought is a bummer. I am guessing they have some issues with getting it right on iOS. Hopefully, it is just temporal and they will resolve it soon. For Android developers, it looks like they have pretty good support and even provides a template app. I have to add that there is a fair bit of fine print I need to agree to before I can get access to their SDK. If I read it right, they basically want a licensing fee for using/commercialising their SDK.

Custom Sensors

Both of the above IMU sensors have similar specifications when it comes to measuring acceleration (using accelerometers) and angular velocity (using gyroscopes). The typical measurement range for accelerometers is +/-16g (that’s 16 times of gravitational acceleration), and for gyroscopes, it’s +/- 2000 degrees per sec. For many applications, this configuration is fine. But there might be some cases where higher acceleration needs to be measured and that goes beyond 16g, like shocks or high impact collisions. Or I might need high-speed rotations to be tracked and 2000 degrees per sec is too low, like measuring the spin of a cricket ball or gridiron football (which can come close to 3600 degrees per sec or 600rpm as demonstrated here by Drew Brees).

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Spin rates of a gridiron football during a throw test

As briefly mentioned earlier, hobby electronics stores like SparkFun, Adafruit, or Tindie would be a good place to start when looking for accelerometers and gyroscopes of different specifications. There are also lots of microcontrollers with Bluetooth Low Energy (BLE)  built-in that are Arduino compatible so we can program them with the Arduino software. One that I found pretty handy is this one called Blueduino which comes with a Lipo charger add-on (and add-ons are great) and that can be found on Tindie.

Football sensor

The gridiron football sensor prototype using the Blueduino

Final Word

For those who are in research and possibly need Matlab and software support for building custom Matlab programs, definitely check out Sabel Sense sensors (Australia). Else, I reckon the mbientlab sensors would be a great option for starting a custom development. If I get a chance to trial their Metaclinic platform, I will put up another post. Meanwhile, do drop me a message here if you need assistance or advice in any of the options above and feel free to leave a comment if you know of better/different solutions out there. With that, thanks for reading!

How Technology Helps Measure Soccer Statistics and Tactics

Over the last 5-6 months, I have had different conversations with people who are working on technologies related to soccer. And I recall writing about Tactical Analysis in Soccer for SportTechie some years back and thought I will reshare it here plus add a bit of update as some things have changed since then.

What are some of the Football Tactical Analysis Websites?

Squawka is a tactical analysis web application that provides a platform where one can view real-time and post-match statistics of (almost) everything that goes on in a football match. This includes time of possession, number of passes, number of shots, shot accuracy, chances created, tackles (or duels), blocks (or defensive actions), player stats etc. Match analysis data is presented in a field diagram with coloured dots and lines and heat maps. Those statistics can then be filtered by team and player for various types of analysis – whether it’s comparing player performance or looking at shots from one team or overall team events. A useful feature is the timeline scrolling which allows one to look at specific 5 min blocks of match activity.

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Player Performance Comparison

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Shots – where they were taken and where they landed

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Events Heat Maps

The comparison matrix is another interesting tool on the site that looks at stats over an entire season. For example, one can select five different teams in the 2013/2014 season of the Australian League and compare stats that they are interested in. The stats displayed can be filtered by ‘total for the season’, ‘average per game’ or ‘per 90 metrics’. One can also compare teams from different leagues and different seasons.  

A special metric of this website is the Squawka Player Performance Score which is calculated using a large amount of data. This player performance score is broken down into “attack”, “defence” and “possession” statistics.

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Comparison Matrix Example

Four Four Two also provides match analysis data on their website in their Stats Zone section. It pretty much provides the same data available in Squawka, except the information is presented in a slightly different way and they don’t have a player performance score. The  Stats Zone allows all the match activities of a player to be viewed together in the Overall-player dashboard, instead of having to select the individual events in the Squawka dashboard. {Update: unfortunately FourFourTwo has discontinued Stats Zone due to limited resources}

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Stats Zone and what their Summary Statistics used to look like

Another site called Outside of the Boot writes commentaries and analysis on selected matches and supports their analysis using statistical data from the above two websites. Other than breaking down the statistics and what was going on in each match, they give reviews on the general style and tactics of a team, player or coach.

Where and how are the data collected?

Regardless of how the data is presented, what’s important is the reliability of the data and where their source is. Interestingly, both sites get their data from Opta, a sports data company that collect, package, analyse and distribute live data. Opta briefly explains on their website that their data collection process is labour intensive with three performance analysts assigned to each match; with one collecting all of the home team actions, one doing the away team and a third analyst checking the data for consistency and adding additional layers of data. They then run a full post-match check within 48 hours to ensure that the database is as accurate as possible.

But what exactly does each analyst do? By using their proprietary software, each Opta analyst puts in the live video feed of a match, then by using hotkeys, every activity that involves the ball is “tagged” – this “tagging” or tracking will record the time each activity started and ended and the X-Y coordinates of the start and end positions. For those who have used video analysis software like SportsCode (now owned by Hudl) or Dartfish, this will sound familiar. But what Opta has done is standardize their activity definition and tracking methods, so every analyst is trained to tag or code the exact same way. This means consistency in the data, allowing every match and every player to be compared using the same standards. The cool thing is, by feeding in historical matches (like all the past world cup matches), they can compare the performance of players from different decades. Check out this video that talks a bit more about what Opta Sports do:

Are there alternative (automated) technologies?

There are a number of athlete tracking technology out there that are either based on wearable technology (Catapult Sports, Tracktics, Polar Team, STATSports & SPT etc) or camera and image processing technology (Stats SportVU and TRACAB). The advantage of wearable sensors is that they can accurately track each athlete’s acceleration and impacts (in three axes) and some even track the players’ heart rate – something that is not possible with any of the current camera or video technology. But data from wearable sensors typically belong to the teams and not shared unless there is an arrangement with broadcasters. With Stats, they claim to not only track real-time 2D (X-Y) positioning data of the ball and the players, but its complex algorithms can also analyse and work out information like speeds, distances, possessions, passings, defence stats and turnovers. So technically, automating tactical analysis to some extent is possible but how much information can be made publicly available is another question.

Some final thoughts

The technology and methods used in Tactical Analysis in football have become more widespread over the years (and its still growing). The statistics that are made available can not only give punters additional information for betting, it can add new dimensions to watching each game. It provides viewers with a better understanding of what the players are actually doing (individually and as a team) and how they have been performing over a season with an unbiased quantified evaluation. For coaches and team managers, it means their decisions (in terms of training, strategising or even talent identification) don’t have to rely too much on gut feel but can be supported with numbers. How much they want to trust those numbers is another thing altogether.

If you know an exceptional app or technology in tactical analysis that is not mentioned here or maybe its still in development, feel free to leave a comment about it, and finally, thanks for reading!


Here are a few other related articles and blogs for those who like geek out a bit more on the topic:

  • Different Game: https://differentgame.wordpress.com/
  • Paper on big data and tactical analysis in elite soccer: link
  • Paper on tactical analysis using pattern recognition: link
  • Paper on a new tactical metric that looks at effective play: link

Do Force Platforms, Pressure Sensors And Smart Insoles Do The Same Thing?

Force platforms, pressure sensors and smart insoles are all devices that a person can step on and get some insight related to their weight or the pressure they are exerting on those devices with each step. Other than that, they are quite different and can have very different applications. This post is just an attempt to break that down. Feel free to jump to the different sections that are of interest:

[Force PlatformsPressure SensorsSmart InsolesSummaryMore on Smart Insoles]

Force platforms

A Force Platform (FP) is an equipment that you would typically find in a lab – an engineering lab, a biomechanics lab, gait analysis lab, ergonomics lab.. you get the idea. They are great for measuring forces applied directly onto its surface. So when a force platform is placed on the ground, you could step on it to find out how much force you are exerting on the platform. For those platforms that measure multiple axes, you could also slide an object across the platform to measure resistance forces between the surfaces. In sports engineering, FPs enable studies in walking/running gait, jumping (and landing), friction measurements in water polo balls or shoes or gloves, the coefficient of restitution of balls, aerodynamic drag (when placed in a wind tunnel), and more.

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An example of a Kistler Force Platform (blue) set up in a wind tunnel

For anyone keen to explore what else is done with force platforms in sports engineering, feel free to do a quick search on these journals: Sports Engineering JournalSports Technology Journal or Journal of Sports Engineering & Technology.

Inside Force Platforms

The majority of Force Platforms in the market are set up with multiple Strain gauges or Piezoelectric sensors/elements that deform proportionally to the applied load. There is also the not so common Hall Effect sensing Force Platform which doesn’t require an external signal amplifier/conditioner like the strain gauges and piezoelectric sensors do. They are typically quite expensive and their prices vary with the number of sensors, size, construction, and additional data acquisition (or signal amplifier) systems.

For those who can’t afford the expensive systems and is adventurous enough to try and build something, a sports physics researcher from the University of Sydney wrote a paper providing details of a cheaper home made force plate. Essentially he used Piezos that were manufactured for sonar applications and they cost $25 each. A quick search on Instructables also showed one DIY instruction on making a strain gage force plate. For the slightly less adventurous, there is also the option of the Wii Balance Board as a cheap force plate alternative. There have been some validations of the gaming platform as a standing balance assessment tool, a golf swing analysis tool, and for use in other medical applications. The only downsides of the Wii Balance Board are the user weight limitation and that a custom software is required to access and read the data.

Pressure sensors

There are three main differences between Pressure sensors and Force platforms. Pressure sensors are typically flexible and can be placed on flat or curved surfaces, unlike Force platforms that have to be mounted rigidly. The other difference is pressure sensors do not measure force vectors. Thirdly (or a slight extension of the second), Pressure sensors only quantify pressure that is perpendicular to it (single axis) so it cannot determine shear forces or friction between two surfaces. Due to their flexibility, pressure sensors have been used to determine comfort and fit in aircraft seats for Paralympians, analyse medical mattresses, measure the pressure of grip during a golf swing, pressure distribution on bicycle handlebars, and more.

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Single force sensitive resistor (FSR) from interlink electronics

Pressure sensors are mostly made out of either resistive sensors or capacitive sensors. The main differences between them are the sensing material used and their electrodes. They can be constructed as single sensing nodes or they can also be constructed in a row-column array fashion. The advantage of the array or matrix construction (over single nodes) is that it requires fewer connections. In an array, the intersection between each row and column is a sensing node. So a 3 by 3 array creates 9 sensing nodes while only needing 6 connections.  On the other hand, 9 single sensing nodes will need 9+1 connections where the +1 is the common ground. The difference becomes much bigger as the number of sensing nodes increases (For example 100 sensing nodes can be achieved using a 10 by 10 array that needs 20 connections or 100 single sensing nodes that need 101 connections).

Single Sensor Nodes Vs Arrays 2

A simple illustration of Single sensing node Vs Sensor Matrix/Array

However, the matrix construction is not without its challenges. The matrix sensor circuit is prone to parasitic crosstalk (capacitive or resistive). This means when pressure is applied on one node or multiple nodes, the electrical readings for other (unactivated) nodes might be affected. This is also known as “ghosting”. Unless some correction is applied, the measurements/readings become inaccurate and potentially useless. Also, the bigger the matrix, the more complex the correction. But if accurate absolute readings are not required, then it’s fine.

A related side story

I have been following the development of this smart yoga mat that was successfully crowdfunded on Indiegogo back in Dec 2014. Fast forward to 2017, they are still struggling to deliver the product. Looking through their updates, we can see they had to deal with sensor accuracy (possibly the crosstalk or ghosting issue); and on top that, some other issues they had include sensor durability, mat materials suitability, and accuracy of their tracking algorithms (which they are using some form of AI). Having prototyped a smart exercise mat around the same time they started, I can fully understand the challenges and why it is taking that long. Then again I am not sure it is worth all that effort. Personally, I think that simply relying on a pressure sensing mat to monitor and give (technique) feedback on yoga poses (or any exercises) has its limitations. Adding camera tracking (possibly utilising the camera on the tablet) might help. That saying, it is not stopping others from developing similar products as seen in this video.

Smart Insoles

Smart Insoles or Instrumented Insoles are essentially pressure sensors made in the shape of a shoe sole. The sensors are usually made in a similar fashion described earlier. Most of the Smart Insoles are also built with IMUs so that it adds a bit more context to the pressure data such as whether the wearers are standing, walking, running or jumping. The greatest advantage of Smart Insoles is they allow feet pressure mapping and measurement on-the-go. Things like continual gait analysis and activity monitoring, and it even has medical application likes foot ulcer prevention and falls prevention.

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Source: Footlogger.com

There are a couple of shoemakers that designed their shoes with the Smart Insole embedded within the shoe like the Altra IQ for running and the Iofit for tracking golf swing stance. The good thing about them is they have designed everything to fit properly into a shoe, made for a specific function. So users don’t run the risk of their Smart Insole not fitting properly into their shoes and collecting inaccurate measurements. On the other hand, users are restricted with specific shoes for pressure monitoring or activity analysis.  But at the end of the day, the pros and cons are really dependent on the individual.

Brief Summary

Going back to the question: “Do Force Platforms, Pressure Sensors and Smart Insoles do the same thing?”; there are some things that they are all capable of performing (e.g. gait analysis), but they all do it in a different way.  Also, there are certain measurements or monitoring that are unique for each sensor. Here’s a simple table that sums it up:

Sensors Measures shear force Measures Pressure Doesn’t require rigid mounting Portable Tracks Motion
Force Plates X X ✔/X
Pressure Sensors X ✔/X X
Smart Insoles X


More about Smart Insoles

Personally, I feel that Smart Insoles is a great idea, with many useful applications in sports and health. Over the last few years, there has been an increase in research and development in this area with many patents generated in the process; and companies around the world have come up with commercial products around the concept of Smart Insoles. It is definitely still in its early stages and I am not sure if it has even reached Early Adopters yet. Sadly, one company that I followed (Kinematix) has already closed shop due to a lack of funding. Perhaps it is ahead of its time like the adidas intelligent running shoe with intelligent active cushioning. Nevertheless, I believe the potential (of Smart Insoles) is there and I think targeting specific niches/problems will probably have a better outcome than designing for a generic application.

If you have an idea or project needing a smart insole or custom pressure sensor, feel free to contact us or leave a comment. We might be able to help you with it or at least point you in the right direction. As always, thanks for reading!

This post also appears on sportstechnologyblog.com: link.


Other related articles:

The challenges of making Smart Sports Garments

What is a Smart sports garment?

Smart sports garments or smart performance garments is a relatively new product segment in the consumer sports tech market. There are probably different views of what the definition should be, but for the purpose of this post, it is a sports garment with embedded sensors/electronics. The main functions of sports garments include providing covering, protection, comfort, ease of movement and some might say making the athlete more aesthetically pleasing. Then with the added sensors and electronics, there generally are two different types of secondary functions.

The more common one is the passive function where sensors monitor stuff on an athlete, either physiological measurements or physical movements. It can make smart evaluations based on the data and give real-time feedback suggesting to the athlete that they should push harder or rest or correct their technique etc. But the decision to act on that suggestion still lies with the athlete or coach. There is also the not-so-common active function where the garment does something to the user. For example giving electrical muscle stimulations (EMS) or possibly electric shocks. But so far the “electric shock” feature is only found on a wristband and hasn’t extended to any other wearables yet. I am not sure why that is the case. For EMS, it has been said that it helps with muscle strengthening which is good for rehab or as a complementary training tool. But I will not go into it since it’s beyond my area of expertise.

R&D in Melbourne

A while ago, I had the opportunity to be a lab rat for a mate’s PhD thesis. He has developed a patented novel technology to measure muscle activity and hopefully able to predict the risk of muscle and knee injuries in elite athletes. The experiment I took part in was basically collecting a bunch of data from this novel sensing technology, wireless electromyography (EMG) sensors, a motion capture system, and a bike trainer. Unfortunately, it also involved me pedalling for my life.

How is this relevant to smart garments? Well, the novel sensors and EMG sensors were all hidden under a compression garment with motion capture markers secured on the outside. The compression tights ensure that the sensors remain where they are (and reliably capture data) and they also (coincidentally) facilitate motion capture. Albeit it was a very crude way of combining the sensors and the 2XU tights, it was a functional prototype (of sorts), and the ultimate goal would be to have those novel sensors built into compression tights.

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Lab rat in action

As we discussed further on commercialising this novel sensing technology for smart sports garments or developing smart compression garments with any wireless sensors, it became apparent that there are a number of challenges. Here’s just a few:

Washing and durability :: A sports garment is going to get sweaty and smelly a lot more than everyday garments. So it definitely needs to get washed. Most smart garments in the market have an electronics module (IMU, BLE module, battery etc) that is removable because they will not survive a tumble in the washing machine. However, there are still conductive pads or conductive yarns (for electrical connections). Would long term washing affect their conductivity and so usefulness?  (A research has shown that most conductive threads will be affected although some hold up better.)

Sensor data accuracy :: In order to capture accurate & robust data, the sensors have to be positioned in the correct location each and every time the smart garment is put on. For measuring stuff like heart rate or EMG, it needs to maintain skin contact for proper measurements. If sensor positions are off (by a bit too much) or skin contact is not maintained, the data collected becomes meaningless and cannot be compared with previous data sets. Not to mention the effect of sweat on EMG electrodes.

Custom fitting :: This relates closely to the above point. Most sports compression wear are made in standard sizes. Sometimes one might find their compression garment being a bit too long at the legs or too short for the arms or too tight around a joint and too loose at a certain spot. It’s fine on a regular compression garment. But when sensors come into play, especially when there is fabric type of sensors (that measures compression or stretch), perhaps a custom-fit garment could be a more optimal solution.

Application :: This is possibly the most important challenge – designing a smart sports garment that solves a real need. It could be a very niche area or a wide-spread problem. But the starting point would be talking to athletes, coaches and sports scientists, to identify where the need is or what needs to be tracked. Then the smart garment that is developed would be a solution and not just a cool piece of technology.

What’s in the marketplace

Having said that, over the last 4-5 years, more than a handful of companies have taken up these challenges and developed their own smart sports garments. A quick search on google shows that there are at least 5-6 smart sports garments in the market.

Brands / Companies
Measured parameters
Heart rate Breathing frequency EMG Motion 3D motion (joints)
OmSignal
Hexoskin
Athos
Myontec
Heddoko

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OmSignal and Hexoskin have smart garments that are an extension of heart rate monitors with an added IMU (Inertia measurement unit) which provides parameters such as breathing rhythm, running cadence, step count and more. While they both seem to be generic fitness trackers when they first came out, it looks like Omsignal has now dropped their original Omshirt and focused on a women-specific product (the Ombra) for running. This might have to do with a review like this: link.

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Myontec and Athos are smart compression garments with surface EMG sensors. The point of putting on these garments is for the user to know what’s going on with specific muscle groups during their run, cycle or gym workout. Myontec is focused on the lower body (quadriceps and hamstring) with an emphasis on running and biking, while Athos covers the whole body looking at general strength training. It is cool that their accompanying software/app provides feedback of which muscles should be activated more during a squat (or other exercises) but I think it might be better if they could correct a user’s posture/technique that is causing the wrong muscles to be activated.

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Heddoko is a full body compression suit that measures a user’s 3D motion much like the Xsens suit. The difference is that the Heddoko suit uses less number of IMU and has embedded stretch sensors, which makes it unique. Assuming the measurements are accurate and repeatable, it has lots of potential applications in sports biomechanics and injury prevention. But based on this video, they are still validating their sensors and trying to work out specific applications.

Some additional thoughts

On one hand, it is cool that there is all these performance tracking technology available to the average athlete – such as wireless EMG and 3D motion analysis (again, assuming the measurements are robust). On the other hand, I wonder if the benefits would outweigh the costs because they are mostly quite expensive and I am not sure if the average gym goer would need that much information about their workout. Perhaps they would be more useful to elite or professional athletes, especially where professional teams have coaches and sports scientists to analyse the data, and give custom feedback. They could also couple it with video playback and analysis so that there is more context to the data.

I think for the average athlete, a smart garment might be useful if they are going through physical rehab and need to monitor certain movements or muscle groups while under the guidance of a physical therapist. Or if they are trying to pick up a specific skill like throwing a football or baseball (In fact, there are sensor embedded sleeves that do just that, which I might discuss another time). Basically, there should really be a specific ‘pain’ to solve. A smart garment with a generic health and fitness application is probably not going to be of much use. Wristbands and smart watches already try to do that.

Do you already own a smart sports garment or are thinking of getting one? If yes, do leave a comment. I would love to hear your thoughts and what you would use it for. Thanks for reading!

Tracking & Managing Anxiety in Athletes Using Wearables

The 2016 Rio Olympic games as with the previous games was a great platform for many tech companies to showcase their latest developments. There are radar and camera technologies that capture motion/biomechanics of an athlete on the field and in the pool. There are wearable devices that (also) track motion plus monitor physiological parameters 24/7. They aim to positively alter athlete behaviour and optimise performance. There are also sports apparel and equipment that were designed and developed (after much R&D) to enhance athlete performance. But we will leave that for another time.

Wearables for tracking performance

Going back to wearables and tracking systems; they often look at (somewhat) straightforward parameters – joint positions, speed (or velocity), height, acceleration, impact, angles, rotation rate, heart rate, heart rate variability, sleep and other physiological stuff. Sometimes coaches and athletes only need to look at a single parameter while other times they may need to examine a combination of variables and find correlations or visualise them over time to identify trends. Some companies go further by processing the above data and coming up with (trademarked) indexes such as Player-Load (Catapult), Windows of Trainability (Omegawave) and Recovery Score (Whoop). What they are trying to achieve is break down all the data that is being collected and deliver one metric that simplifies things and make it easy for coaches and athletes to measure performance (and recovery) .

In major games like the Olympics, where athletes trained years to prepare and qualify for that one event and possibly one moment, there can be a lot of anxiety and pressure to perform. Even if all the physical preparation has been done right, the results could still boil down to how well those emotions are managed; the difference could be between a podium finish or not performing as well as expected. So are there wearable technologies that monitor an athlete’s emotions and maybe warn the athlete of dangerous anxiety levels that can lead to choking or panic?

Wearables for tracking anxiety

Turns out there are a number of wearables in the market that do that. Here are three different types:

  1. Head-worn wearables that measure EEG signals (or brain activity) like the Emotive Insight and Muse. Although the Muse is designed as an aid for meditation and relaxation, it is basically monitoring four EEG channels to see how excited or relaxed a person’s brain is. The Emotive Insight has five EEG channels and looks at the user’s cognitive performance in areas such as Engagement, Focus, Interest, Relaxation, Stress, and Excitement. Emotive also has a higher spec neuroheadset that can look at fourteen EEG channels and goes into much more depth of what’s going on in a person’s mind and how he/she is feeling.

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    Emotiv Epoc+: 14 channel wireless EEG system

  2. Wrist-worn devices that measure electrodermal activity (or EDA), blood volume pulse, skin temperature and motion; like the Feel and Empatica E4 wristbands. Based on research, measurements of EDA strongly reflect sympathetic activation which is linked to stress levels and excitement. Measuring heart rate variability through the blood volume pulse sensor also reflects sympathetic and parasympathetic activation. Skin temperature is another reliable measure of stress levels as shown in this research. Finally, motion tracking with inertial measurement units (or IMUs) helps identify the user’s activity and tries to place a connection between anxiety levels and what the user might be doing at that time.

     

     

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    The Empatica E4 and Feel: 4 sensors packed on a wrist device

     

     

  3. Clipped-on devices that measure breathing frequency like the Spire. The Spire is built with force sensors; when it is secured onto the user’s waistband or bra, it detects the expansion/contraction of the user’s torso and diaphragm during breathing, thus deriving the breathing rate. Then algorithms are used to determine from the breathing waveforms whether the user is calm, tensed or focused.

 

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Spire: Breathing frequency tracker

 

Most of these devices also provide an accompanying app to monitor anxiety levels, and they prompt users to meditate or do breathing exercises. On a side note, a breathing exercise for lung patients was adapted for training athletes’ breathing technique and also focuses on dealing with anxiety. Athletes could also listen to brain.fm music that either helps them relax or stay focused. In a way, managing stress levels on a day-to-day basis can be beneficial for athletes because stress levels can increase the likelihood of an athlete falling sick or getting injured, and it also affects recovery.

Emotion Profiling for Performance

On the other hand, when it comes to performing well during competitions/races, some athletes actually perform better with some amount of anxiety. In fact, different athletes in different sports may perform better at varying levels of anxiety. In other words, some athletes perform well at high levels of arousal while others may perform better at lower levels of anxiety. It’s all about finding a sweet spot. As mentioned in this article, one widely used tool by coaches/athletes to identify that sweet spot or optimal performance zone is the individual zones of optimal functioning (IZOF) model. This is a qualitative analysis approach that involves the athlete recounting the emotional experiences related to successful and/or poor performances. All the emotions are then labelled and rated as described here, and this creates an individualised emotion profile showing which emotions are helpful for performance and which ones are unhelpful. Of course, this would only work if athletes have competed for a number of times previously and came out with different outcomes (winning or losing or setting new personal bests).

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Individualised emotion profiling (source: sportlyzer)

Ultimately we could utilise all the different wearables (and tools) mentioned above and somehow piece all that data together to shed some light on the inner workings of each individual athlete. Then the data could be used to “pivot” them in the optimal direction. But at the end of the day, its really down to the athletes themselves pushing hard every day and fighting battles with their body, mind and soul to get to where they would be. So let’s just salute the Olympic athletes for what they do and what they have achieved. And while we await the start of the Paralympics, I leave you with this video below by Under Armour and Michael Phelps. Thanks for reading!

Versus Fitness: Developing A Smart Gym

VersusOver a year ago, I wrote a post about developing with the Kinect and how I was working on a project that revolved around it. Fast forward to today, the project is now an officially launched gym that is also known as Versus Fitness.

What is Versus Fitness?

Versus is a system that has gamified fitness. By utilising different sensors and technologies, it is able to measure 3D motion, pressure, force, acceleration and power output of over 200 different gym exercises (and counting). With each proper repetition (or rep) that is executed, the user not only gets the rep counted by the system, a score is given based on the above measured parameters, and the score is scaled based on the user’s weight and height. In that way, 2 people of different weight and height doing the same workout can compete against each other on almost equal terms (Hence the name Versus). In case the term “wearable technology” comes to mind, no, there is nothing that the users need to wear to get their exercise tracked (maybe except a heart rate monitor, but that is purely optional). Just check out the video below.

How I got involved?

I started working on the Versus Fitness gym since late 2013 and it was purely by coincidence. Someone who knew Brad Bond (the founder of Versus Fitness) was at the RMIT Sports Engineering Lab on one of those Uni open days and he saw a novel sensor technology that would suit Versus. After a series of meetings and discussions, a research contract was set up to further develop that technology for Versus. This was partly funded by the Victorian Technology Development Voucher. At the same time, they were also looking for an additional team member to work on motion tracking algorithms. That’s where I came into the picture. Long story short I was offered a contract role on the Versus project which was partly funded by the Enterprise Connect – Researchers in Business grant (this has been replaced by the Entrepreneurs Infrastructure Programme). Kudos to Aaron Belbasis who was a key connector/initiator who brought everyone together and who was also one of the key researcher who helped develop the novel sensor tech. There’s a bit more details about the RMIT-Versus collaboration here.

What Tech are we talking about here?

One of the sensor technologies came from the research collaboration mentioned earlier. The team at RMIT calls it a “sensor-less sensing platform”. The closest thing would be Force Sensitive Resistors (FSR) like the ones from Tekscan. If you had a proper look at the video above, you will see the “sensor-less sensing platform” used in the floor exercises and some of the running exercises. Basically its a sensor that measures pressure.

There are other sensors that were developed or customised for tracking motion and a number of them are available off the shelf or at least purchasable online. In fact some of the sensors (like load cells and accelerometers) are similar ones typically used in the manufacturing, or automotive industry. A lot of custom fittings, enclosures and mechanisms were designed for the sensors before they could be installed in the gym. Majority of the design were done in-house and prototyped with the help of a MakerBot replicator.

But what really made the sensors (tracking system) worked effectively are the smart algorithms that processes all the sensor data and accurately identifies when each person is performing the exercise properly and evaluates how well he/she has done it. Initially when designing the algorithms for tracking each type of exercise, it all seemed pretty straightforward; but as things progressed, it turned out there were quite a few more considerations – e.g. filtering out “incorrect” movement data that resembled an actual rep, or profiling movement data from users of different abilities (or fitness level) etc.

Perception & Reality

Another important part of the system is the “gaming interface” or the “gaming control centre”. It is the personal trainer’s assistant. It relays to the users what exercises to do, records their performance, stores the performance data in a database, reminds the user how well they did previously (their Personal Best), manages the equipment (to some extent), and ensures that every exercise station is in sync so that the workout runs smoothly. That allows trainers to focus on one of the things they do best: scream at motivate people.

So with the combination of the sensors, smart algorithms and the gaming interface, this means: real-time tracking, with feedback of the users’ performance (score) or technique delivered right after each completed rep, and an overall quantified workout so users know how well they fare compared to their previous workouts (and with other users).

Future Developments?

The very first Versus Fitness gym is based in Moorabbin and that has seven different exercise stations (as seen in the video above). One could call that the full Versus experience. There are a number of possible developments in the pipeline. One is the development of new exercise stations to increase the type of exercises that can be tracked. Also, there are possible opportunities to customise the system for the elite or professional athletes, or even rehabilitation applications. Something that is definitely in the works is a “multi-station” concept – a single exercise station that has several sensor solutions allowing tracking of a few different types of exercises (e.g. dumbbell, kettlebell & floor exercises). This significantly reduces the footprint of the equipment and would suit small gym spaces. In fact this is currently on trial in a gym somewhere in Australia, and depending on how things go, you might start finding the VS logo in many more places!

Of Racing Suits and Aerodynamics

Wind Tunnel tests with custom designed mannequins and different Under Armour speed skating suit prototypes.

In many sports that involve high speed movements, drag or air resistance is probably one of their biggest enemy in achieving their peak performance. One winter sport that faces this challenge is speed skating, and turns out altitude plays a big part as well – the higher the skating venue is, the less air resistance there is (more about that in this article). Also the effect of drag on the skater’s speed and performance is pretty significant and the suit that the skaters wear could have an impact on the colour of the medal they get.

So just before the 2014 Sochi Winter Olympics, there was a bit of news about the revolutionary speed skating suit designed and made by Under Armour and Lockheed Martin. The “Mach 39” was supposed to be the fastest speed skating suit ever made. Unfortunately, instead of delivering medals (gold ones for that matter), the result was the US athletes performed below expectations. Now, this could be due to the suit OR if we break it down, could be due to a thousand other reasons (on top of the suit)..

There was a bit of history to the design of the suit, and the basic idea was: just as dimples on golf balls reduced aerodynamic drag, adding dimples on the suit would have the same effect. Of course, other than the dimple design, there were other considerations like textile selection and compression fitting design. Just have a look at the video below that describes what the designers and researchers looked at to reduce friction and improve aerodynamics of the suit. What’s really interesting is how they customised the mannequins to typical skating positions for wind tunnel tests. (Drag to 4:00 of the video to just see the custom mannequins)

Although the rational behind the design and testing all seems to make sense, I can’t help but have a few questions:

a. With so much movements during speed skating, is it really possible to estimate the drag based on wind tunnel experiments? I mean, there are a number of sports that do drag tests in wind tunnels; like skiing and cycling. But these sports have moments of competing when the athlete maintains a certain position for a short period; and those are the moments where having an optimum position (aerodynamically) could really reduce drag significantly. But speed skaters hardly stay in one position during competition (maybe except at the starting line). Then if that’s the case, would the wind tunnel results be fully applicable on the track?

b. Friction plays 2 roles: it slows you down and it gives you more grip/control. If there is too much friction, it impedes movement; but if there is minimal or close to no friction, the athlete might lose control. How then, do we strike a balance between them?

c. Is it possible to measure drag dynamically on the track? Well, a company called Alphamantis seems to have done that, but with cycling, and in a velodrome fitted with gate sensors. Some additional input parameters they require include the bike’s wheel circumference and also inputs from standard power meters and speed/cadence sensors. With the power meters, there is a calibration process before the actual aerotesting where they apply a model to calculate drag. For more details of the testing, you can read ths interesting blogpost by DCrainmaker.

I reckon it is possible (in theory) to develop a model for speedskating (similar to what Alphamantis did for cycling) to estimate drag on the ice skating track. The model might be slightly similar to this one in wheelchair racing: when the speedskater is pushing off (and at equilibrium), there are 4 different forces applied on the speedskater: 1) Reaction force, 2) Inertia, 3) Friction between the ice and skates, and 4) Drag force.

  1. Reaction force (or applied force) can be measured by instrumenting the skates with a shoe sole pressure sensor similar to this or this.
  2. Inertia can be determined by measuring the forward acceleration of the skater (using an inertia sensor or a suit of sensors), then multiplying that by the overall mass of the skater.
  3. Friction can be calculate based on the coefficient of friction of ice which is different for straights and curves according to this paper.
  4. Finally, since the sum of all these forces equals to zero, we can determine the drag force!

Xsens Concept Tests in Speedskating

Of course this model is very much simplified and some assumptions are made, but if more thought is put into it, this might just work.

Anyway, going back to the lacklustre results of the Under Armour Mach 39 suit, there could be so many reasons why the athletes didn’t perform during those races. Since US speedskating has extended the contract with UA, they obviously know that the suit wasn’t the main culprit. It did sound like the athletes weren’t really used to the new suit, so maybe it’s just a matter of ‘breaking-in’ the suits.

Thanks for reading and if you have any thoughts or suggestions on aerodynamics or drag tests, do leave some comments!

(Also posted in SportsTechnologyBlog.com)

Swimming with the times

InstabeatSwimming is one of the top priority sports in Australia and has been one of the most successful sports in the international arena. As such there’s a lot of attention put into improving the performance of athletes. In fact, for those who are new to this blog, research in swimming performance is one of the focus areas of Queensland Sports Technology Cluster (QSTC), and you will find some recent published work here and some related blog posts about them here. There has also been lots of work done in various research institutes in Australia and here are some notable ones in the last 4-5 years:

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Mini-Traqua in action

The AIS itself has set up the Aquatic Testing, Training and Research Unit (ATTRU), where there has been even more research and testing done on swimming research, often working in tandem with research institutes mentioned earlier above. These and other similar type of research and innovation is what will give the Australian swimmers the edge to win on the international stage. Some of these research outcomes stay at the elite level of sport because they may not be relevant to the casual swimmers or do not have any commercial application or they are just ‘secret squirrel’ stuff. But some of the developed technology do get commercialized, though it may take a while before they get released into the public, but they do.

Commercialized Sports TechSo what kind of technologies/gadgets are available to everyday swimmers today?

1. Lap and stroke counting. How many times have you swam in a pool and lost track of the number of laps you covered? It can be pretty annoying. That’s why engineers developed swimming specific wrist watches that counts strokes and laps. These watches have motion sensors that enable them to count strokes, laps, and even estimate speeds and distances. Some of these include: the FINIS Swimsense, the Swimovate Poolmate, the Speedo Aquacoach, and the Garmin swim. The Garmin Swim particularly could even identify the type of stroke (front crawl, butterfly or breast stroke).

2. Music while swimming. One way to do it is to blast music at the swimming pool (assuming its your own pool, or everyone else at the pool likes your taste of music). The other option is to use waterproofed mp3 players. Some companies have developed swimming specific mp3 players, some applied waterproofing technology on existing devices, some made waterproof cases. Most of them did not stray far from the original mp3 player designed for land dwellers, all except the FINIS SwimP3 which used Bone conduction technology for audio transmission instead of earphones. If anyone is keen on swimming with music, they should check out DCrainmaker’s post comparing all (most of) the swimming mp3 players.

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DCRainmaker with the AquaPulse

3. Heart Rate monitoring. For the more serious athletes who want to monitor their heart rates to keep track of how hard they are training (or if they are training in the correct zone), there are two options available in the market right now – Heart rate belts and Heart rate ear clips. Heart rate chest belts are a pretty common training accessory for most athletes, but not all heart rate monitoring (HRM) belts will work in the water. For example, HRM sensors that transmits via bluetooth (or any higher frequencies) will not work in water. So if you want to use a HRM chest belt for swimming, make sure they transmit in water (i.e. lower frequencies). As a guide, Polar sensors and the PoolMate HRM sensors will work. The alternative to chest belts is ear clips, and the only product in the market is the FINIS AquaPulse which uses infrared sensors to monitor capillary blood flow at your earlobes. The advantage of using the ear clip (I believe) is it is more secure than the chest belt which tends to slip while swimming thus losing heart rate readings. Although I can’t imagine the ear clip sensor being very comfortable during swimming.

4. GPS. This is mainly for open water swimming. Tracking where you have swam in the open ocean/sea/lake/river/pond. Many sports watches (targeted at runners and triathletes)  have a built-in GPS module. That’s your Garmin, Suunto, Timex, Polar, Magellan, Nike etc etc. But one GPS sports watch that stands out is the Leikr, because it actually puts the map on your wrist. Coloured maps! It’s not officially out in the market yet because it started as a Kickstarter project, but it has been successfully funded so it won’t be long. Would you really need the maps? It depends and I think it’s arguable.

5. Performance feedback. The traditional way of getting feedback is to have a coach scream at you. But with all these gadgets that count your stroke rate per lap, calculates how fast you swim and monitors how hard (heart rate) you are training, a swimmer can train without a coach yelling at him/her every session. These devices can tell you how you are performing. Since most of the mentioned devices are watches, the main feedback form is displaying all the calculated statistic on the screens. The one device that sets itself apart is the FINIS Aquapulse which used its Bone Conduction technology (what they used for their swimming mp3 player) to provide audio feedback of your heart rate. Saves you the trouble of trying to catch a glimpse of your watch face. Too bad it doesn’t work together  with their swimsense watch to also give you audio feedback of how many laps you swam and how fast you are swimming. Although that might make it worse than having a coach yelling…

So just when you think: that should be pretty much what swimmers need to help them train; along comes Instabeat – a heart rate sensor that is mounted on your goggles (and any other goggles), measures the laps, turns, breathing pattern, and gives you heads-up visual feedback of your training. Other than music and GPS, it does most of the things mentioned above. But how is it different from the rest?

  • For one, it measures heart rate from your temporal artery using optical sensors (which is patent-pending). 
  • Secondly, it becomes part of your goggles, so you are not wearing or clipping on an extra thing on your body.
  • Thirdly, it determines your breathing pattern. This is something new.
  • Lastly, it gives you real-time visual feedback of your heart rate training zone so you know if you are meeting your goals.

What led Hind Hobeika (Instabeat founder) to develop this was her deep dissatisfaction with existing heart rate monitors in the market. Utilising her swimming experience and engineering knowledge, she went through several designs, prototyping and testing them and the final result is this revolutionary heads-up display design.

Left: Initial designs of the Instabeat; Right: The final Instabeat design

Some of the challenges the Instabeat team faced included getting the right data from the sensors, coming up with a design that could fit all the different goggles, and not forgetting the challenge of making the sensor waterproof – the nemesis of all wearable technology. And now that they are past those product design challenges, they face the next challenge which is to bring it to market. They have decided to go through Indiegogo to crowdsource funds and you can support them here. The response looks positive so far and you know the Instabeat team is a bunch of forward thinkers because they have already planned a next version which includes wireless (bluetooth) data transfer and syncing with your smartphone. I even found out [Spoiler alert] that they would explore adding GPS for open water swimming and possibly make a version compatible with other eyewear, i.e. sunglasses. Sounds like the Sportiiiis could be having some competition in the near future.

In the meantime, I leave you with Instabeat’s pitch on Indiegogo:

Thanks for reading!