Tag Archives: heart rate

Mark Drangsholt on Understanding His Heart Rhythm Disorder

Mark Drangsholt has been dealing with an issue with his heart since he was a young man. Since his early twenties, when he as diagnosed with paroxysmal atrial tachycardia he’s had to deal with irregular heart rhythms. In this talk Mark explains how the transition into adulthood negatively impacted his health and then how he used self-tracking and a focused athletic program to help him reduce his weight and improve his health. Most show&tell talks would end there, but Mark still had the irregular rhythm issue to deal with. After what he describes as an episode that made him think, “This is it. I’m going to die.” he decided it was time to apply his self-tracking process in order to understand his heart rhythm disorder and possible triggers. Mark also decided to go one step further and apply the principles of case-crossover design to his tracking methodology. Watch his talk below and keep reading to learn a bit more about why you might want to consider using case-crossover design in your self-tracking projects and experiments.

The following excerpt from the QS Primer: Case-Crossover Design by Gary Wolf provides a great background for his method:

Mark’s self-tracking data didn’t naturally fit with any of these approaches. To understand whether these triggers actually had an effect on his arrhythmias, he used a special technique originally proposed by the epidemiologists Murray Mittleman and K. Malcolm Maclure. A case-crossover design is a scientific way to answer the question: “Was the patient doing anything unusual just before the onset of the disease?” It is a design that compares the exposure to a certain agent during the interval when the event does not occur to the exposure during the interval when the event occurs.

Using this method, Mark discovered that events linked to his attacks included high intensity exercise, afternoon caffeine, public speaking to large groups, and inadequate sleep on the previous night. While these were not surprising discoveries, it was interesting to him to be able to rigorously analyze them, and see his intuition supported by evidence. “A citizen scientist isn’t even on the conventional evidence pyramid,” Mark notes. “But you can structure a single subject design to raise the level of evidence and it will be more convincing.”

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QS Gallery: Bill Schuller

Today’s QS Gallery entry comes to us from Bill Schuller. Be sure to check out his blog, Data Obsessive, to learn more about this visualization and other interesting self-tracking projects.

A driver made a left turn from a stright-only lane right in front of me as I was proceeding straight through the intersection from my straight or left lane. I have occasionally turned on the accelerometer and gyro logging in FluxStream Capture while I drive. This time around, I have even more data. You can see the massive deceleration and the associated spike in my heart rate and drop in my beat spacing (RR). I haven’t pulled my GPS data yet, but I was able to spot this easily in the FluxStream graph. Those dips in the Acceleration data really stand out. Interestingly, my heart rate also reflects my mood afterward.

Initially relieved that I didn’t get hit this time, then enraged that it had nearly happened again, calming slowly as I composed in my head a letter to the City of Addison imploring them to add more signage at that intersection.

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Hands Free Heart Rate Tracking

A quick post here to highlight some interesting developments in the heart rate tracking space. Tracking and understanding heart rate has been a cornerstone of self-tracking since, well since someone put two fingers on their neck and decided to write down how many pulses they felt. We’ve come a long way from that point. If you’re like me tracking heart rate popped up on your radar when you started training for a sporting event like a marathon or long distance cycling. Like many who used the pioneering devices from Polar it felt a bit odd to strap that hard piece of plastic around my chest. After time, and seeing the benefits of tracking heart rate, it became part of my daily ritual. Yet, for all the great things heart rate monitoring can do for physical training, there have been very few advances to provide people with a noninvasive method. That is, until now.

ThearnWebcamPulse

Thearn, an enterprising Github user and developer, has released an open source tool that uses your webcam to detect your pulse. The Webcam Pulse Detector is a python application that uses a variety of tools such as OpenCV (an open source computer vision tool) to “find the location of the user’s face, then isolate the forehead region. Data is collected from this location over time to estimate the user’s heartbeat frequency. This is done by measuring average optical intensity in the forehead location, in the subimage’s green channel alone.” If you’re interested in the research that made this work possible check out the amazing work on Eulerian Video Magnification being conducted at MIT. Now, getting it to work is a bit of a hurdle, but it does appear to be working for those who have the technical expertise. If you get it working please let us know in the comments. Hopefully someone comes along that provides a bit of an easier installation solution for those of us who shy away from working in the terminal. Until then, there are actually quite a few mobile applications that use similar technology to detect and track heart rate:

Let us know if you’ve been tracking your heart rate and what you’ve found out. We would love to explore this space together.

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More Quantified Self Tools at CES: A Second Look

Last week we brought you a look into some of the interesting Quantified Self tools that were debuted at CES. Here are a few more we noticed from the deluge of CES coverage. Thanks to MobiHealthNews, Gizmodo, Engadget and many QS friends for the tips.

body-analyzer-front-webWithings Smart Body Analyzer (WS-50)
The latest wireless scale from Withings adds some interesting new sensors: resting heart rate, ambient air quality (CO2) and room temperature. The combination of physiological and environmental monitoring, while simple in this case, opens many new possibilities for Quantified Self projects.
Measures: Weight, BMI, Fat Mass, Heart Rate, Room Temperature, Room CO2

 

 

The Zensorium TinkeTinke  is a small sensor and companion app for iOS devices dedicated to helping users understand their health and wellness. This is a really interesting variation on the emerging theme of Heart Rate and Heart Rate Variability self-monitoring. The Tinke has no battery and no screen. Instead, the small optical sensor plugs directly into the iPhone.
Measures: Heart Rate, Heart Rate Variability, Blood Oxygen, Respiratory Rate

 

A similar approach is used by the Masimo iSpO2ispo2, where the focus is on blood oxygenation.
Measures: Blood Oxygenation, Heart Rate, Perfusion Index
Salutron

 

 

 

mia_alpha

Mio Alpha
The Mio Alpha boasts of continuous and strapless heart rate measurement. Using technology developed by Phillips, the Alpha uses optical heart rate sensing at the wrist and a soon to be released mobile app. What once seemed like difficult technical magic is on the verge of becoming commonplace.
The Mio Measures: Heart Rate
Sync: Bluetooth 4.0

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Quantified Self at CES: Digital Pedometers Add Wireless Heart Rate Tracking and More

I’ve been curious about tracking physical activity since I was an undergraduate. I remember traveling to a local middle school with a researcher interested in how physical activity was taught in low-income Native American communities. Back then, the best we could do was have the children wear simple electromechanical pedometers to count their steps during their physical education classes. Fast forward about ten years and I’m still working with pedometers and physical activity sensors – but much better ones. Quantified Self toolmakers are experimenting with many upgrades to the old digital pedometers, including new ideas about syncing, more fashionable design, and – of particular interest to self-trackers – integration of optical heart rate monitors. (No chest strap.)

Below are some of the notable Quantified Self tools recently announced at CES. Did I miss one? Let me know in the comments and I’ll add it! I’ve also written a bit about what I think are some notable trends below.

Fitbit Flex
The Flex appears to be Fitbit’s answer to the growing trend of wrist worn wearable activity monitors. Interestingly they’ve chosen to focus on the wireless syncing capabilities and eschew a traditional display; there is just a small glanceable LEDs to highlight goal progress.
Measures: Steps, Distance, Calorie Burn, Activity Minutes, Sleep Time, Sleep Quality
Sync: Bluetooth 4.0

 

Withings Smart Activity Tracker
In 2013 Withings is stepping in to the activity tracking space with their Smart Activity Tracker. While it appears to be just another accelerometer-based device Withings has also packed a heart rate pulse sensor into the small form factor.
Measures: Steps, Distance, Calorie Burn, Sleep Quality, Heart Rate
Sync: Bluetooth and Bluetooth 4.0

 


Omron Activity Monitor
Omron has long been a staple in the low-cost pedometer market. With the launch of their Activity Monitor they’ve shown up with a wireless activity tracker of their own. Omron is semi-wireless; syncing requires that you plug a USB accessory into your computer, then place the pedometer nearby.
Measures: Workout Time, Steps, Distance, Calories burned, Pace
Sync: NFC Plate (USB)

 

Omron Heart Rate Monitor
Integration of pulse tracking  into activity monitors is a current trend, and we’re very curious about what we’ll learn from having continuous heart rate data. Omron’s new heart rate monitor uses optical sensing on a strapless watch, with eight hours of storage capacity. The press announcement promises pace, calories, and distance, which means the watch probably has accelerometer-based actigraphy on board as well.
Measures: Heart Rate, Pace, Distance, Calories Burned
Sync: Micro USB

 

Fitbug Orb
The Orb is new small and sleek device that builds on their already released Fitbug Air wireless pedometer. The new pebble-like Orb is a screenless activity tracker that uses Bluetooth syncing to a mobile app in three different modes: Push for updates on demand, Beacon for timed updates on a regular interval, and Stream for real time updating. The Orb’s small form factor works with a variety of different wear options, including wrist straps and lanyards.
Measures: Steps, Distance, Calories Burned, Sleep
Sync: Bluetooth 4.0

 

BodyMedia Core 2
The BodyMedia armband is known for its accurate activity tracking, which comes from integrating the data off multiple sensors. A new device, the Core 2, has the same measurements that are currently available (core temperature, heat flux, galvanic skin response, and tri-axial accelerometry) in a smaller package. A version with an integrated heart rate monitor will be also be available.
Measures: Temperature, Heat Flux, Galvanic Skin Response, Activity, Heart Rate (optional)
Sync: Bluetooth 4.0

 

Bonus Non-Activity Device

HapiLabs HapiFork
This last device kept popping up on my various feeds yesterday. The HapiFork is designed to help you understand how you eat by tracking how many bites you take and how long it takes you to eat your meal. It will also alert you when you’re eating too fast.  Will the first person to use this please give a Quantified Self show&tell talk as soon as possible?
Measures: Fork “servings”, Eating Time
Sync: Bluetooth or USB

 

In my current work I’m really interested in how real time information about physical activity behavior can be used to help people change their normal patterns. In our little corner of the research world we understand that self-tracking devices are wonderful tools to help people change their behavior. But, what we don’t know yet is how the data gathered by these tools can really help people in the moment. The newest crop of tools and devices may start to help us answer that question.

By now if you’ve seen one physical activity tracker then you’ve seen them all. At their core they use the same technology that’s been used for almost a decade – actigraphy. That is, most devices are based on an accelerometer, a tiny little sensor that measures gravitational force acceleration. These sensor pass data through an algorithm that used machine learning and pattern recognition techniques to determine a variety of data points. Steps, distance, activity intensity, calorie expenditure – you’re probably familiar with all these. So what’s new in this space? How are companies starting to differentiate themselves? While looking through some of the new offerings being showcased at this week’s International Consumer Electronics Show (CES). It appears that there are two major themes that I think are coming forth: Wearability and Syncing

Wearability. The pedometers we made kids wear 10 years ago? Utilitarian hunks of plastic and electronics. Nothing you would want to show off to your friend or coworker. Looking at the latest from Fitbit, BodyMedia, and others it’s clear that companies are introducing real fashion where there used to be just electronics. Will they succeed in making activity trackers a fashion trend? A status symbol?

Syncing Capabilities. When Fitbit introduced their tracker a few years ago one of the biggest complaints was that it didn’t sync to our phones. Now, nearly every new device offers Bluetooth syncing with paired mobile apps. The rise of Bluetooth 4.0 has made it easier for nearly everybody to wirelessly sync. I’m curious about the future of low power data sharing beyond the phone. Soon we may see myriad devices talking to each other directly. What happens when your fitbit starts talking to your fridge?

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Steven Jonas: Stress Out Loud

Steven Jonas discovered through an EEG assessment that he had a strong “freeze” response to stressful situations. This inspired him to use his emWave to monitor his stress levels, hack it to alert him whenever he got too stressed, and change his patterns at work. Check out Steven’s open, inspiring story in the video below, filmed at Quantified Self Seattle, as well as his slides.

Steven Jonas from David Reeves on Vimeo.

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Toolmaker Talk: Hind Hobeika (Butterfleye)

At a recent QS-themed event at Stanford, 3-time Tour de France winner Greg LeMond described the constant stream of new technologies that make bicycles lighter and more streamlined and that provide ever more detailed monitoring of the cyclists. In contrast, innovation in swimming seems limited to controversial bathing suits. Competitive swimmer Hind Hobeika aims to change that with Butterfleye, as she describes below and in her talk in Amsterdam last fall. She is also inspiring tech entrepreneurship in Lebanon, and is the organizer of the Beirut QS meetup group.

Q: How do you describe Butterfleye? What is it?

Hobeika: Butterfleye is a heart rate monitor for swimmers:  a waterproof module that can be mounted on all types of swimming goggles and that visually displays the athlete’s heart rate in real-time. Butterfleye has an integrated light sensor that measures the heart rate by reflection from the temporal artery (a ramification of the carotid artery that runs through the neck), and a 3 color LED that reflects indirectly into the goggle lens indicating the status relative to the target: green if the swimmer is on target, red if above target and yellow if below target.

Butterfleye is still in the prototyping stage, I am currently working on iterating the design to get to a market product.

Q: What’s the back story? What led to it?

Hobeika: I used to be a professional swimmer during my school and university years, and all of the trainings were based on the heart rate measurement. As a matter of fact, in all professional trainings, there are 3 main target zones that are dependent on a percentage of the maximum heart rate, and that lead to different results from the workout: the swimmers try to stay between 50-70% of their maximum heart rate for fat burning, 70-85% for fitness improvement, and 85-95% for maximum performance. In every single workout, the coach used to combine different sets of each of the zones to make sure the swimmer gets a complete workout and works on different aspects of his body. The problem was that there was no effective way of actually measuring heart rate during the practice! What we did is count the pulse manually after each race. Other options would have been to wear the watch + belt or use a finger oximeter, but both of these were very impractical for a swimmer.

I built the first prototype during the ‘Stars of Science’ competition, which is kind of like the Arab version of the ‘American Inventor’ initiated by Qatar Foundation. Following a Pan-Arab recruitment campaign, I was one of the 16 candidates to get selected among 7,000 initial applicants to go to Doha for the competition. Once I got to the Qatar Science and Technology Park, I was able to combine my passion for swimming and my background as a mechanical engineer, along with the experts and the resources available in Education City to build the first concrete version of my idea. After four long months, I won the third prize, and got a valuable cash award that I used to file for a US patent, start a joint stock company in Lebanon, and hire an electronics engineer and an industrial designer to get started on the prototyping process.

Q: What impact has it had? What have you heard from users?

Hobeika: The product is not on the market yet, so the reactions I have been getting so far are from swimmers and athletes hearing about the idea or testing the first prototype.

Swimmers I have talked to have commonly agreed that there is a very big lack of monitoring tools for practice in the water, and that Butterfleye would be filling a very big gap. As for people who have tested it, they are surprised of how lightweight it is and how they don’t feel it when wearing it in the water.

Here is my assumption on the impact Butterfleye will have: Swimming is a very solitary sport, and it is very difficult for athletes to get feedback on the performance if swimming without a coach or a team. It is the main reason why most people prefer practicing another activity. Having a practical monitor that can not only measure the heart rate but give all kind of information a swimmer would want to know (such as lap counting, stroke counting, speed, distance, etc.) will encourage more people to practice this complete sport and change its status of ‘solitary’.

Q: What makes it different, sets it apart?

Hobeika: Butterfleye is innovative when it comes to its sensor design: it is the first heart monitoring tool that doesn’t require wearing a chest belt, a finger clip or an ear clip, elements that would add a lot of drag in the water, and that would be cumbersome for the swimmer. Butterfleye’s sensor is integrated in the module itself, and measure the heart rate from the temporal artery.

Butterfleye’s design is also one of its competitive advantage: it is specifically designed for swimmers. It is waterproof, modular- it can be mounted on any type of goggles, light-weight and in the shape of a waterdrop in order to minimize the drag. It is also flat so it doesn’t interfere with the swimming motion. It is designed to be perfectly compatible with the biomechanics and the dynamics of swimming.

Butterfleye also stands apart by comprising a waterproof heads-up display, where the swimmer can visualize his target zone on his lens. This way, the swimmer would not have to interrupt the motion of his arms (as he would do if he was wearing a watch), and could visualize the heart rate in real-time, compared to using a pulse ox right after the race.

Swimming technology, unlike all of the other sports, is widely unexplored to date, especially when it comes to monitoring and self tracking devices. Butterfleye is one of the first tools to tackle this market gap.

Q: What are you doing next? How do you see Butterfleye evolving?

Hobeika: My next target is to release a first version of the waterproof heart rate monitor in the market. After that, comes a series of other monitoring products for the swimmers, so they would be able to track calories, strokes, lap count, etc.

I am also planning on expanding this platform technology to models compatible with running, skiing, biking and diving.

Q: Anything else you’d like to say?

Hobeika: I participated in ‘Stars of Science’ when I was still a university student, and after winning the third prize I got a job at a renowned Lebanese engineering design firm. I was very scared of working full time on my project and giving up the sense of security I had, and was only able to do it a year down the line.

The entrepreneurship ecosystem is still very nascent in Lebanon and in the Middle East, and I am part of the first generation that is working on a hardware startup in the region. It is very challenging, simply because there aren’t many (or any) resources available. I have to ship and prototype everything abroad, which makes the entire process more lengthy and expensive.

However, I am also part of that generation who will, through our projects, develop and nurture the right resources to make it easier for the next crazy change makers! I am already working on a website An Entrepreneur in Beirut, which is a platform for all the resources needed for hardware development in Lebanon.

Product: Butterfleye
Website: www.butterfleyeproject.com
Price: tbd

This is the 16th post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned?  In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences? If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta at rajivzume@gmail.com.

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Numbers From Around the Web: Round 6

There is something really magical about taking data and turning it into a compelling visual image. Even though I’ve already written a bit about the importance of making data visual, I am consistently amazed at how data can be made more appealing and informative by creating eye-popping graphics. Today we are devoting this NFATW post to some amazing projects with beautiful data.

Tom MacWright is an engineer for MapBox and Development Seed and spends his time creating and using amazing visual representations of his data. Here are just two of many wonderful projects.

A New Running Map

Tom wasn’t happy with the data visualization he was getting from his Garmin GPS and heart rate watch so he decided to build his own using tools he works with every day. What came out was a really interesting interactive website that visualizes his running routes along with his heart rate. Click on the image above to play around with him data.

He’s also created a unique representation of the same time of running data (GPS + HR) that anyone can play with called Ventricle. Ventricle allows you to plot your own running data if you have .gpx files.

A run plotted on Ventricle by Tom MacWright

Minute

I’ve had a long standing interest in how I spend my time interacting with my computer. As a long time RescueTime user I’ve gotten used to having something watching my computer use and informing me about my habits. Tom was also interested in his computer use, but wanted something that had less functionality while still giving him information that was important. So, he developed Minute, a keystroke counter and visualization system that constantly records and displays the keystroke frequency over time.

Tom MacWright's keystroke visualization

By using a heat map he is able to better understand the pattern of his technology usage. Interestingly, he is also able to make inferences about his sleep and leisure time as he treats them as the inverse of his keystroke time:

Minute is an open-source application hosted on github so if you’re interested in understanding your own computer use or want to contribute to the project go take a look at the source code.

We’ll wrap up today with a quote from Tom’s post on what he learned from developing and using Minute:

Tracking nearly anything you do is alarming and humbling. The aggregates of our actions are lost on us: we can watch hundreds of hours of television and write it off as a small time commitment. How much is too much? It’s hard to make pretty charts without learning something and thinking about what they should look like.

Every few weeks be on the lookout for new posts profiling interesting individuals and their data. If you have an interesting story or link to share leave a comment or contact the author here.

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Kiel Gilleade: Lessons from a year of heart rate data

Kiel Gilleade researches physiological computing. He streams his heart rate data to Twitter, live, 24 hours a day. Over the course of a year, he learned how his heart rate responded to different events, dietary intake, and changes in routine. He was also surprised to learn that he didn’t get up until 8 am! His friends and colleagues can check in on how he’s feeling by looking at his data, but context is very important to record and display for a complete understanding. In the video below, Kiel shows his entire year of data in one beautiful, final slide. (Filmed at the QS Europe conference in Amsterdam.)

Lessons from a year of heart rate data by Kiel Gilleade from Quantified Self Amsterdam on Vimeo.

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Toolmaker Talk: Alexander Grey (Somaxis)

The first speaker at last week’s QS meetup in San Francisco was Alexander Grey. He told us about the muscle-activity sensor he had developed and the fascinating things he had learned about himself from using it. The result of many years of thinking and work, he’s now eager to find collaborators, so he jumped at my suggestion to participate in this series.

Q: How do you describe Somaxis? What is it?

Grey: We have developed a small, wireless sensor for measuring muscle electrical output. The sensors stick onto the body adhesively (like Band-Aids) and transmit data to our smartphone app. One version “MyoBeat” uses a well established heart metric to provide continuous heart rate measurement (like a “chest strap” style sensor). A second version “MyoFit” uses proprietary algorithms to measures the energy output of other muscles. For instance, one on your quads while running can give you insight into how warmed up you are, how much work you are doing, fatigue, endurance, and recovery level. If you use two at the same time, it can show you your muscle symmetry (when asymmetry develops during exercise like running or bicycling, it can indicate the onset of an injury). Our goal is to get people excited about understanding how their bodies work.

Q: What’s the back story? What led to it?

Grey: My parents used to run a clinic that used muscle energy technology (sEMG) along with a special training method called Muscle Learning Therapy to cure people with RSI (Repetitive Strain Injury) and other work-related upper extremity disorders involving chronic pain. Each sEMG device they bought cost them $10K. I started to develop early symptoms of TMD (Temporomandibular Joint Disorder) when I was only 10, and my father used sEMG to teach me how to control and reduce my muscles’ overuse. The training worked, and I still have it under control today.

Years later, I decided to start a company to develop and commercialize  more accessible / less expensive sEMG technology, with my mom as my investor. (My father has passed away, but I think he would have supported the idea.)  At first we were going after a workplace safety service — I developed an algorithm that quantified people’s likelihood of developing an RSI injury in the future, and envisioned a prevention-based screening/monitoring service to offer to progressive companies. The feedback I got from VCs was that we needed to start with a bigger market. So we redesigned the product to make it small, cheap, and completely wireless. I also started working on a new set of sports-related algorithms to interpret muscle use into useful metrics.

Q: What impact has it had? What have you heard from users?

Grey: Having this new kind of tool at my disposal has really been a lot of fun, and has allowed me to run some new kinds of experiments that haven’t really been practical before.

For example, I wondered: for a given running speed, what cadence or stride rate would use the least energy, and so delay the onset of fatigue? I put sensors on my both quads, hamstrings, and calves. I created an audio track that increased from 120 – 170 bpm in increments of 5pm, 15 seconds on each. I kept my treadmill locked at 6.5 mph (my “comfortable pace”). By adding up the work done by all 6 muscles in the legs, I got a snapshot of the energy expenditure at each stride rate / cadence. The resulting curve [see graph above] answered my question: for me, at 6.5 mph, 130 bpm is my “sweet spot” that minimizes energy expenditure. It also showed a second trough in the graph, not as low as 130, but still pretty low, at 155 bpm. So if I need to run uphill or downhill, and want to keep the same speed but take shorter steps and still try to minimize energy burn as much as possible, I should shoot for 155 bpm.

Another test that these tools allow us to do is to figure out how recovered someone is from exercise. I did a test where I ran at a fixed speed every 24 hours (that’s not enough recovery time for me – I’m not in good shape). The first day, the muscle amplitude was about 1000 uV RMS (microvolts, amplitude). The second day, the amplitude started out at 500 uV and decreased from there. So the lack of sufficient recovery showed up in the data, which was quite interesting to see.

Whenever we have volunteers in the lab offering to help out (runners, usually) they geek out over these devices and the insight that they can get into the muscles of their bodies for the first time. We’ve had about 40 volunteers help out with muscle data gathering, and about 60 with heart rate testing.

Q: What makes it different, sets it apart?

Grey: Our design goals for our sensors are “good enough” data, wireless, long battery life, and comfort (wearability). Key to this is using a low-power, low-bandwidth radio. The trade-off is a much lower sample rate and a/d resolution than medical-grade sensors. Our sensor transmits processed data, not the raw data. However, our data is good enough for sports and fitness, where you want to see some predigested metrics and not raw graphs or frequency analysis. The benefit is that our battery life is 100 hours, and our sensor is small and light enough to attach using an adhesive patch. The up-side of an adhesive-based solution is that one-size fits all, it’s very comfortable, and there is no tight and annoying strap around your chest.

Q: What are you doing next? How do you see Somaxis evolving?

Grey: We are mainly focusing on improving the physical sensor itself: rechargeable battery, completely waterproof (current version is water resistant), and a smaller size. And maybe a medical-grade version with much higher sample rate and a/d resolution.

We also want to open up the hardware platform so that others can develop applications for it. For example, maybe someone wants to develop software for Yoga that uses muscle isolation to help do poses correctly. Or perhaps someone wants to focus on a weight-lifting application that assesses power and work done during lifting. We can envision many possibilities for sports, gaming, physical therapy, and health.

Q: Anything else you’d like to say?

Grey: I would love to hear from anybody who has ideas about potential uses of our technology! Also, we are fairly early-stage, so if anyone wants to work with us (individuals) or partner with us (companies) we definitely want to hear from you. You can reach me at agrey@somaxis.com

Product: MyoLink platform: MyoBeat (heart) and MyoFit (muscle)
Website: www.somaxis.com (coming soon – there’s nothing there right now, but check back again soon)
Platform: Sensors stream data to an iPhone app (Android under development) and certain sports watches (Garmin, etc.)
Price: $25 for a starter set of 1 Module (MyoBeat or MyoFit) and 4 adhesive patches. Or you can buy 1, 2 or 3 Modules, with a one-year supply of patches, for $75, $125, or $170, respectively.

This is the 11th post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned?  In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences? If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta at rajivzume@gmail.com.

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