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Running Sensors

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[[File:Running Sensors.jpg|right|thumb|300px|A selection of the running sensors I've tested. From top left: [[Moxy]], [[BSX]], [[Wahoo TICKR Run]], [[Lumo Run]], [[TgForce]], Garmin [[Running Dynamics]], [[SHFT]], [[MilestonePod| MilestonePod v2]], [[MilestonePod| MilestonePod v3]], [[Stryd]], and a Gu for size comparison.]]There are a growing number of wearable devices that will analyze your biomechanics, mostly from small startup companies, though the bigger players are also contributing to the space. Many of these devices a making use of the cheap and accurate accelerometers that are now readily available, though there are some other approaches being used. These are cheap accelerometers have created an explosion of products, and it seems likely that we'll see a number of companies fail. Here are my sound bite summaries:* [[Stryd]] is a running sensors that I think every runner should have. It's the most accurate way of measuring distance and pace, and has integration with a wide array of running watches. Its estimate of [[Running Power Meters| "Running Power"]] is moderately useful.* Garmin's [[Running Dynamics]] is well worth having if you own a Garmin watch that support supports it, though I wouldn't buy a Garmin just for its support of Running Dynamics.
* [[RunScribe]] provides lots of detailed and useful information, but I consider it a 'running lab' rather than an everyday training tool.
* [[MilestonePod]] is amazingly cheap and provides a wealth of data. It's worth the cost just for its ability to track the miles you put on your shoe, but it adds in more data than most other systems that cost many times as much.
* [[Wahoo TICKR Run]] give gives some useful interesting metrics, but you have to use their Smartphone App to get them. Their "3D Smoothness" would be awesome if it worked. It's also a Heart Rate Monitor that supports both Ant+ and Bluetooth.
* [[Moxy]] can provide a new way of evaluating exercise intensity by looking at the oxygen saturation of the blood within the working muscles. However, not only is it expensive, but you'll also need to dedicate significant time and effort into getting the best out of it.
* [[TgForce]] is a "one trick pony", but it's a great trick. It measures the [[Impact]] on the lower leg rather than the foot, providing great real time metrics. Sadly , there are production issues at the moment that are causing the sensors to fail.
* [[Moov Now]] This is a cheap and interesting sensor. Like the TgForce it can measure lower leg [[Impact]], but it's got software problems that have not been fixed.
* [[Lumo Run]] Needs more development before it's ready for prime time.
{{:Running Sensors-table}}
=What To Look For In A Running Sensor=
Having tested a fair number of running sensors, I think there are 3 aspects of the metrics that a sensor provides that you should consider.
* '''Accuracy'''. Not unreasonably, a running sensor should provide a reasonably accurate metric. Depending on the metric, the value could have some degree of error without affecting its value if the error is always proportional. For instance, if a sensor gives a value for Ground Contact Time that is always 10% too high, that may be perfectly acceptable as you can look for relative changes. Or a sensor could have a synthetic value of "smoothness", which might not be based on a real-world measurement, but could still provide actionable information. Of course, accuracy is always preferable, and an inaccurate sensor could cause more problems than it solves. A Cadence sensor that reads 10% too high might lead you to believe that your Cadence is fine when it's actually far too low.
* '''Responsive'''. A useful metric needs to be responsive enough that you can see the results of any changes to your running form. A metric that has too much smoothing can be quite frustrating, while one with too little smoothing can be so twitchy that it's equally useless. Of course, the responsiveness also depends on the feedback method, and a metric that you only get in post run analysis is far harder to use.
* '''Meaningful'''. A valuable metric is one that has some meaning to you as a runner, either because it has a bearing on your [[Running Economy]] or because it may have a bearing on your injury risk. The current state of the available research doesn't provide a huge amount of confidence linking many of the available metrics to either injury rates or Running Economy, but there are some that seem to have potential.
* '''Actionable'''. The final characteristic of a valuable metric is one that you have some control over. For instance, Cadence is relatively easy to change and therefore the metrics are actionable. Other metrics may be rather tricky to modify with your running form, such as a braking force (at least, I found it very hard to change that metric.) Another reason why a metric may not be actionable is because correlation is not causation. For instance, lower Ground Contact Time is associated with a better Running Economy, but it's not clear if reducing Ground Contact time will directly improve Running Economy, or if there is some other variable that is responsible. (My personal suspicion is that improvements in Running Economy are more related to Cadence, which in turn changes Ground Contact Time. I'd like to see research into Ground Contact Time normalize the values against Cadence.)
=Stryd=
''Main Article: [[Stryd]]''
 
The Stryd Footpod is my favorite running sensor. It provides vastly better distance and pace information than any GPS watch I've tested. This alone makes it well worth the purchase price and if for any reason I lost mine, I'd replace it immediately and without hesitation. Stryd is primarily marketed as a "running power meter", though I think this sells it a little short. [[Running Power Meters]] are somewhat flawed concept, as they are really an estimate of power, and the estimate is of far less value than a cycling of power meter is to a cyclist. That said, I found that Stryd provides a useful way of providing even effort on uphill sections (but not down hills.) It also has the best watch integration of any running sensor.
=Garmin's Running Dynamics=
''Main Article: [[Running Dynamics]]''
Many newer Garmin watches ([[Garmin 620| 620]], [[Garmin 920XT| 920XT]], [[Garmin Epix| Epix]], [[Garmin Fenix 3| Fenix 3]], etc.) combined with a special chest strap will provide extra metrics that can give insight into your Running Form. The Garmin watches will provide these metrics in real time, allowing you to see the effect of changes in your form. These metrics include:
* Vertical Oscillation. This is how much the torso moves up and down with each stride. It is generally believed that less [[Vertical Oscillation ]] is a better, but I suspect that this is an oversimplification. It's sometimes a thought that a greater vertical oscillation [[Vertical Oscillation]] will result in greater [[Impact]], but this is not the case. [[Impact]] is how quickly you decelerate, so landing hard can result in less vertical movement but a shorter, more intense deceleration. It's even suggested that greater vertical oscillation [[Vertical Oscillation]] will result in more braking force, but that does not seem reasonable. I believe that some are part of a runners vertical movement is likely to be elastic in nature (consider a bouncing rubber ball), some of the vertical motion will be while the runner is airborne (ballistic), and some of the vertical motion is the vertical deceleration as the runner lands. So it seems likely to me that excessive vertical oscillation [[Vertical Oscillation]] is bad, but it's a tricky to know what excessive is likely to be, or how to correct it.
* Ground Contact Time (GCT). [[The Science of Running Economy]] generally shows that longer Ground Contact Time is correlated with poorer [[Running Economy]].
* Ground Contact Time Balance. This is the relative Ground Contact Time ratio of the left and right feet, which will reveal potential imbalances in the body.
* Computed metrics. The Garmin watches will use the basic metrics to calculate things like stride length (based on cadence and pace), and Vertical Ratio (vertical oscillation [[Vertical Oscillation]] to stride length ratio).
[[File:RunningDynamics.jpg|none|thumb|300px|Garmin's Connect web site shows the metrics gathered using the HRM4 and [[Garmin Fenix 3]].]]
=RunScribe=
''Main Article: [[RunScribe]]''
[[RunScribe]] is a small pair of [[Footpod]]'s that provide a wide variety of [[Foot Strike]] metrics. These include things like [[Impact]] G's, GCT, Braking G's, [[Pronation]], and more. I love the detailed metrics that are provided, and the insight into my running form, and possible imbalances. The main disadvantage with the RunScribe approach is that the data is not available during the run, and has to be analyzed afterward. RunScribe is rather more sophisticated than most Footpods as it not only has a 3-axis accelerometer, it also has a 3-axis gyroscope and a 3-axis magnetometer allowing it to sense far more movement. You can read about my testing at [[RunScribe]].
[[File:RunScribe.jpg|none|thumb|500px|An overview of the data from RunScribe]]
=MilestonePod=
''Main Article: [[MilestonePod]]''
[[MilestonePod]] is a vastly cheaper alternative to RunScribe, and while it doesn't provide the detailed analytics, it's a great value for money. It's also a cheap and effective way of keeping track of the mileage of your shoes, and is worth its price for that feature alone. Like [[RunScribe]] the MilestonePod doesn't provide real-time metrics, and you have to analyze the results post run. You can read about my testing at [[MilestonePod]].
{| class="wikitable"
|- valign="top"
=TgForce=
The TgForce measures just one thing; the peak [[Impact]] on your lower leg. While this is a far cry from the broad array of data gathered by devices like [[RunScribe]], TgForce may add some particularly valuable insight. Measuring the [[Impact]] that the foot can be a little misleading as the movement of your ankle can absorb a significant portion of that shock, so knowing how much of the force is transmitted to your lower leg may give a much better insight into injuries. The [[Impact]] that your lower leg (tibia) receives will be transmitted into your knee, so reducing that stress might be quite helpful. The companion app only runs on iOS devices, not android, which will limit the appeal for some, and unless you buy two devices, it will only measure one leg at a time. Even if you get two devices, it doesn't appear that the app readily supports this approach, unlike [[RunScribe]] that does a lot to provide side to side comparisons. That said, I really like to have real-time feedback, something that TgForce provides, either visually for use on a treadmill, or audibly outside. I've ordered a TgForce and my initial testing shows that the data from TgForce might be quite valuable, but there is a quality control problem and I've had several sensors fail. They have a fix and I should have a fully working sensor soon.
[[File:TgForce1.png|none|thumb|250px|This is the real time display, showing the [[Impact]] of each step (from one leg) in the bar graph, plus the current and average [[Impact]]. There are also metrics such as total steps and [{[Cadence]].]]
=Moov Now=
''Main Article: [[Moov Now]]''
The [https://www.amazon.com/dp/B00KLAGSW8 Wahoo TICKR Run] is a chest strap based system that's similar to Garmin's [[Running Dynamics]]. It supports both Bluetooth and Ant+, which is nice, but most of the functionality beyond heart rate requires you to have your phone with you on your run. If you do, then you get Cadence, Ground Contact Time, Vertical osculation, and 3D smoothness. This 3D smoothness shows the jerk (rate of change of acceleration) in three planes; forward-backward, up-down, and side to side. This has great potential, but the smoothness depends far too much on the tightness of the strap, even varying with your breathing.
[[File:WahooSmoothness.png|none|thumb|250px|The smoothness that Wahoo displays seems like it could be really valuable if only it was usable.]]
=Lumo Body Tech Run(Bankrupt) =
''Main Article: [[Lumo Run]]''
'''Update: Lumo has gone bankrupt and as far as I can see their sensors are effectively bricked. Unlike BSX, who made some of their software open source, Lumo has just disappeared. '''Like many other devices, [[Lumo Run]] uses accelerometers to measure body movement, but uniquely (so far) Lumo places the accelerometers at the small of your back. This allows Lumo to not only detect [[Cadence]] and [[Vertical Oscillation]], but also breaking and pelvic movement. The measurement of braking force is rather different from [[RunScribe]], as Lumo measures how much your overall body slows up with each stride, rather than measuring the deceleration of your foot in touch down. I believe that both approaches are important, and give valuable insight into possible biomechanical problems. In addition, Lumo will measure how much your hips (pelvis) will drop from side to side, and how much it rotates (twists). Lumo is available Lumo Run is available for <jfs id="B01K22SOYE" noreferb="true"/>. I really wish that Lumo would measure [[Impact]], as it would be great to know how much of the foot strike [[Impact]] reaches the hips.
{| class="wikitable"
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|[[File:LumoPostRun.png|none|thumb|250px|After the run is complete, Lumo displays some summary statistics.]]
|}
=SHFT=
''Main Article: [[SHFT]]''
 
The SHFT system uses two pods, one on the chest and one on the foot. The SHFT system includes some unusual metrics such as toe off angle and body angle, as well as Cadence, GCT, Vertical Osculation, [[Impact]], Braking, and Foot Strike. They also claim to measure [[Running Power Meters| power for running]], but my testing suggests this is far from useful. The system requires you to carry your phone, and the main feedback is via audio through the headphones which I generally find rather ineffective. There are some good post run analytics available via the app and on their web site, as well as data export of the basic running information. The price of the two SHFT sensors is $300 which is a little high compared with other systems, but it does provide quite a bit of information. I've found the SHFT metrics are not as accurate as I'd like; read more at [[SHFT]].
[[File:SHFT Pod.jpg|none|thumb|250px|The SHFT pod is delightfully rounded and rather organic.]]
=Sensoria=
''Main Article: [[Sensoria]]''
The [[BSX| BSX Lactate Threshold Monitor]] attempts to estimates your [[Lactate Threshold]] by measuring the oxygen saturation of the blood within your muscles. The results of the first version were extremely disappointing, but I have not had the opportunity to fully test the updated hardware. However, even if the BSX works perfectly, its value is limited by the relative ineffectiveness of [[Tempo Runs| Lactate Threshold Training]]. You can read about my testing at [[BSX]].
[[File:BSX1.jpg|none|thumb|x300px|The dashboard view of the BSX app, showing previous results.]]
=Stryd=
Power meters have helped cyclists for a number of years, providing a valuable metric around how hard the cyclist is exercising. Stryd is attempting to provide a power meter for runners, which superficially sounds like a good idea. Certainly, there are many problems with using Heart Rate to determine training intensity, and measuring VO2 is only practical in a laboratory, so and a power meter could be a better option. However Stryd actually measures movement and then calculates power. The details are a little unclear, as their website does not explain their approach or a well, nor do they seem to be any validation studies that I could find. It seems that Stryd measures Vertical Oscillation, braking and side-to-side (lateral) movement to calculate power, though it also measures Heart Rate and Ground Contact Time. It's a chest strap system, and it seems a lot of the metrics are also gathered by Garmin's [[Running Dynamics]]. It seems likely that you could perform similar calculations using the Garmin system, but I find myself unconvinced by the approach.
=RUNTEQ Zoi=
Zoi places sensors on both the foot and the torso. This allows it to gain a little more insight than other sensors as it knows about the movement of the foot and the torso independently. Eventually I expect to see a company produce a group of sensors placed on each foot, each knee, and the pelvis, which would give insight into the movement and [[Impact]] forces across most of the body. The Zoi only has one Footpod, so it doesn't give you detailed foot strike information in the way that [[RunScribe]] can, though you could see them adding that functionality in the future. The Zoi gives quite a few metrics, including [[Cadence]], Ground Contact Time, [[Vertical Oscillation]], breaking (at the torso, not foot breaking), of [[Foot Strike]] type (fore, mid, heel), Foot [[Impact]], and some [[Pronation]] information. Zoi has a smartphone app that provides real time feedback and post-run analytics, but I've not seen any support for displaying metrics on a watch. Currently Zoi is on pre-order in Europe for 150 EUR. I'd like to test this system if I can get hold of one. The approach is similar to the SHFT system, though the SHFT uses a 9-axis sensor and it's not clear what the Zoi uses.
=RPM<sup>2</sup>=
RPM<sup>2</sup> (Remote Performance Measurement/Monitoring) is a pair of insoles that fit into your normal running shoes. These insoles measure pressure and use accelerometers to measure movement (a little like Sensoria). The details are not entirely clear from the web site, but they claim to measure [[Cadence]], Ground Contact Time, [[Foot Strike]], and "acceleration power". The system also claims to measure running power, though I'm not sure of the methodology. The RPM<sup>2</sup> system measure pressure in four areas (Sensoria has three), giving a [[Pronation]] measurement. There are notes that RPM<sup>2</sup> insoles are not waterproof, which is rather disconcerting, and if you run in different shaped shoes the fitment is likely to be problematic. The sizing of the insoles needs to take into account the position of the ball of the foot to ensure the sensor is in the right place. The system supports both Bluetooth to connect to your phone as is common with running sensors. The RPM<sup>2</sup> can also connect to an Ant+ and Bluetooth so there is both watch, though it's a bit of an ugly kludge. You need to have your phone app with you, and some information that can be displayed on then plug in the Wahoo Key adapter via a lightning-to-30 pin adapter to transmit Ant+ to a watch (it's not clear if this is more than just power). The Wahoo Key and adapter are all extra bits you have to buy. The system can also be used as a power meter for cycling. Their web site is [https://www.rpm2.com Remote Performance Measurement/Monitoring]. =SHFTKinematix TUNE=The SHFT system uses two podsKinematix went out of business in April 2017. =Testing Approach=Where possible, one on the chest and one on the foot, rather I like to verify the Zoimetrics that these running sensors are providing. The SHFT system includes In some unusual metrics cases, this is a fairly trivial, such as toe off angle [[Cadence]] which you can measure by simply counting your steps. Some other metrics I've verified by using High Speed Video (HSV.) This requires a little bit of time and effort, and body anglea lot of attention to detail but it can be quite an effective approach. * '''Ground Contact Time'''. I've used HSV to verify Ground Contact Time, and found more variation than I expected. Using HSV to measure Ground Contact Time you can see the very earliest and latest stages of contact as well as Cadence, GCTestimating the pressure changes from the compression of the foam midsole. Examining the video makes it clear that some devices are including time where the shoe is completely airborne, which is a little surprising. * '''Vertical Oscillation'''. I've evaluated the accuracy of Vertical OsculationOscillation by looking at the movement of my torso using HSV and lasers. This proved to be rather more tedious and time-consuming than I'd anticipated, but the results were worthwhile (to me at least.) * '''Foot Strike'''. I've done some simplistic testing of sensors that measure [[ImpactFoot Strike]]. I've run with these sensors in my usual heel strike, Braking, plus running forefoot both with and Foot Strikewithout my heel touching down. They also claim I've used HSV to measure power for runningverify that my foot strike pattern is what I think it is, something as it's easy to be mistaken. Ididn'd need t include midfoot strike as this is tricky to get exactly right, and tricky to see demonstrated in a lab verify using HSV. This approach to measuring Foot Strike is based around the point of first contact, not the point of highest force. Personally, I believe itthat the latter approach is far more relevant, but harder to measure.* '''Power''s accurate and even then I'm not sure it. It's useful due tricky to the impact of measure [[Running EconomyPower Meters| running power]]. The system requires you without access to carry your phoneVO<sub>2</sub> equipment, and so I've resorted to some simple tests. An incremental treadmill test should show an increase in power with an increase in pace; if it appears doesn't pass that your only feedback is via audio through the headphones which I generally find rather ineffective. It looks like there are some good post run analytics available via the apptest, but no sign of data exportthen it's probably not much use. =Ideas For The price of Future =This section documents a few ideas I've had for running sensors, partly to inspire manufacturers, and partly to disclose these ideas so that they cannot be patented in the two SHFT sensors is $300 which is a little high compared with other systemsfuture. ==Proportional Audio Feedback ==
Many running sensors will provide information on your biomechanics using an audio message. Typically, this is a spoken message such as "you're landing on your heel" or "your braking is 1.31 feet per second." I generally find these audio messages far more annoying than they are useful. The messages tend to occur too infrequently for me to get a sense of how any modifications in my form are changing the metric being measured. The spoken word means it's a little tricky to combine this with music or radio. A better approach is to have a simple signal like a beep when your metric is outside the desired level. For example, [[TgForce]] will beep when your [[Impact]] is too high, and you can combine this simple audio signal with music for the spoken word from a in audiobook or the radio. I believe that a superior approach is to have a variable audio signal that indicates how well you're doing. So instead of having a simple threshold such as 7g you'd have a range such as 5-9g. Then, when your [[Impact]] is above the lower threshold you would get an audio signal, but the audio signal would vary in one or more of volume/pitch/duration depending on where you are in the range. So a 5g [[Impact]] would produce a quiet, short, deep beep, and 9G [[Impact]] would produce a loud, longer, high-pitched beep. This way you'd get quantitive feedback on how well you're doing against your chosen metric.
==Deriving Practical Impact From Acceleration==
Often running sensors will provide a value for impact based on the acceleration measured at the foot or leg. However, the bulk of the stresses on the lower limbs comes from the acceleration of the overall body mass during landing. Therefore, I believe it would be more effective to measure the acceleration of the torso on landing to provide an estimate of the stresses on the lower limbs. I suspect that both peak acceleration and the area under the acceleration curve would provide insight into the stresses of running. Peak acceleration is fairly obvious, and I suspect is more useful than a jerk. However, it may be useful to evaluate the area under the acceleration curve, as the time spent under stress could also be a significant factor on injury rates.
==Measuring Foot Strike==
Several running sensors will measure [[Foot Strike]], though so far, I've only found RunScribe and SHFT to provide useful data. However, even these devices tend to measure the foot angle on initial contact, and I suspect that it would be far more useful to measure foot and call at the time of maximum deceleration of the torso. This requires at least two sensors, one on the torso and another on the foot, and ideal three so there's one for each foot. Synchronizing the timing between the devices is likely to be problematic, but not insolvable.

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