Gym

Microbiomes and a glimpse to doctors becoming a small niche

ianwaring Fitness, Future Trends, Gym, Medical, Software, Statistics Leave a comment

Microbiomes, Gut and Spot the Salmonella

When I get up in the morning, I normally follow a path on my iPad through email, Facebook, LinkedIn, Twitter, Google+, Feedly (for my RSS feeds) and Downcast (to update my Podcasts for later listening). This morning, Kevin Kelly served up a comment on Google+ that piqued my interest, and that led to a long voyage of discovery. Much to my wifes disgust as I quoted gory details about digestive systems at the same time she was trying to eat her breakfast. He said:

There are 2 reasons this great Quantified Self experiment is so great. One, it shows how important your microbial ecosystem is. Two, it shows how significant DAILY genome sequencing will be.

He then gave a pointer to an article about Microbiomes here.

The Diet Journey

I’ve largely built models based on innocent attempts to lose weight, dating back to late 2000 when I tried the Atkins diet. That largely stalled after 3 weeks and one stone loss. Then fairly liberated in 2002 by a regime at my local gym, when I got introduced (as part of a six week program) to the website of Weight Loss Resources. This got me in the habit of recording my food intake and exercise very precisely, which translated branded foods and weights into daily intake of carbs, protein and fat. That gave me my calorie consumption and nutritional balance, and kept track alongside weekly weight readings. I’ve kept that data flowing now for over 12 years, which continues to this day.

Things i’ve learnt along the way are:

  • Weight loss is heavily dependent on me consuming less calories than my Basal Metabolic Rate (BMR), and at the same time keeping energy deduced from carbs, protein and fat at a specific balance (50% from Carbs, 20% Protein, 30% fat)
  • 1g of protein is circa 4.0 Kcals, 1g of carbs around 3.75 Kcals, and fat around 9.0 Kcals.
  • Muscle weighs 2x as much as fat
  • There is a current fixation at gyms with upping your muscle content at first, nominally to increase your energy burn rate (even at rest)
  • The digestive system is largely first in, first out; protein is largely processed in acidic conditions, and carbs later down the path in alkaline equivalents. Fat is used as part of both processes.
  • There are a wide variety of symbiotic (opposite of parasite!) organisms that assist the digestive process from beginning to end
  • Weight loss is both heat and exhaust. Probably other forms of radiation too, given we are all like a light bulb in the infrared spectrum (I always wonder how the SAS manage to deploy small teams in foreign territory and remain, for the most part, undetected)

I’ve always harboured a suspicion that taking antibiotics have an indiscriminate bombing effect on the population of microbiomes there to assist you. Likewise the effect of what used to be my habit of drinking (very acidic) Diet Coke. But never seen anyone classify the variety and numbers of Microbiomes, and to track this over time.

The two subjects had the laboratory resources to examine samples of their own saliva, and their own stool samples, and map things over time. Fascinating to see what happened when one of them suffered Salmonella (the green in the above picture), and the other got “Delhi Belly” during a trip abroad.

The links around the article led to other articles in National Geographic, including one where the author reported much wider analysis of the Microbiomes found in 60 different peoples belly buttons (here) – he had a zoo of 58 different ones in his own. And then to another article where the existence of certain microbiome mutations in the bloodstream were an excellent leading indicator of the presence of cancerous tumours in the individual (here).

Further dips into various Wikipedia articles cited examples of microbiome populations showing up in people suffering from various dilapidating illnesses such as ME, Fibromyalgia and Lyme disease, in some instances having a direct effect on driving imbalances to cause depression. Separately, that what you ate often had quite an effect in altering the relative sizes of parts of the Microbiome population in short order.

There was another article that suggested new research was going to study the Microbiome Zoo present in people’s armpits, but I thought that an appropriate time to do an exit stage left on my reading. Ugh.

Brain starts to wander again

Later on, I reflected for a while on how I could supply some skills i’ve got to build up data resources – at least should suitable sensors be able to measure, sample and sequence microbiomes systematically every day. I have the mobile phone programming, NoSQL database deployment and analytics skills. But what if we had sensors that everyone could have on them 24/7 that could track the microbiome zoo that is you (internally – and I guess externally too)? Load the data resources centrally, and I suspect the Wardley Map of what is currently the NHS would change fundamentally.

I also suspect that age-old Chinese Medicine will demonstrate it’s positive effects on further analysis. It was about the only thing that solved my wifes psoriasis on her hands and feet; she was told about the need to balance yin/yan and remove heat put things back to normal, which was achieved by consumption of various herbs and vegetation. It would have been fascinating to see how the profile of her microbiomes changed during that process.

Sensors

I guess the missing piece is the ability to have sensors that can help both identify and count types microbiomes on a continuous basis. It looks like a laboratory job at the moment. I wonder if there are other characteristics or conditions that could short cut the process. Health apps about to appear from Apple and Google initiatives tend to be effective at monitoring steps, heart rate. There looks to be provision for sensing blood glucose levels non-invasively by shining infrared light on certain parts of the skin (inner elbow is a favourite); meanwhile Google have patented contact lenses that can measure glucose levels in the blood vessels in the wearers eyes.

The local gym has a Boditrax machine that fires an electrical up one foot and senses the signal received back in the other, and can relate body water, muscle and fat content. Not yet small enough for a mobile phone. And Withings produce scales that can report back weight to the users handset over bluetooth (I sometimes wonder if the jarring of the body as you tread could let a handset sensors deduce approximate weight, but that’s for another day).

So, the mission is to see if anyone can produce sensors (or an edible, communicating pill) that can effectively work, in concert with someones phone and the interwebs, to reliably count and identify biome mixes and to store these for future analysis, research or notification purposes. Current research appears to be in monitoring biome populations in:

  1. Oral Cavity
  2. Nasal
  3. Gastrointestinal Organs
  4. Vaginal
  5. Skin

each with their own challenges for providing a representative sample surface sufficient to be able to provide regular, consistent and accurate readings. If indeed we can miniaturize or simplify the lab process reliably. The real progress will come when we can do this and large populations can be sampled – and cross referenced with any medical conditions that become apparent in the data provider(s). Skin and the large intestine appear to have the most interesting microbiome profiles to look at.

Long term future

The end result – if done thoroughly – is that the skills and error rates of GP provided treatment would become largely relegated, just as it was for farm workers in the 19th century (which went from 98% of the population working the land to less than 2% within 100 years).

With that, I think Kevin Kelly is 100% correct in his assessment – that the article shows how significant DAILY genome sequencing will be. So, what do we need to do to automate the process, and make the fruits of its discoveries available to everyone 24/7?

Footnote: there look to be many people attempting to automate subsets of the DNA/RNA identification process. One example highlighted by MIT Review today being this.

Apple iWatch: Watch, Fashion, Sensors or all three?

ianwaring Apple, Fitness, Google, Gym, Low Energy Bluetooth, Medical, Pebble, Watches Leave a comment

iWatch Concept Guess Late last year there was an excellent 60 minute episode of the Cubed.fm Podcast by Benedict Evans and Ben Bajarin, with guest Bill Geiser, CEO of Metawatch. Bill had been working on Smart watches for over 20 years, starting with wearables to measure his swimming activity, working for over 8 years as running Fossil‘s Watch Technology Division, before buying out that division to start Metawatch. He has also consulted for Sony in the design and manufacture of their Smart watches, for Microsoft SPOT technology and for Palm on their watch efforts. The Podcast is a really fascinating background on the history and likely future directions of this (widely believed to be) nascent industry: listen here.

Following that podcast, i’ve always listened carefully to the ebbs and flows of likely smart watch releases from Google, and from Apple (largely to see how they’ve built further than the great work by Pebble). Apple duly started registering the iWatch trademark in several countries (nominally in class 9 and 14, representative of Jewelry, precious metal and watch devices). There was a flurry of patent applications from Apple in January 2014 of Liquid Metal and Sapphire materials, which included references to potential wrist-based devices.

There have also been a steady stream of rumours that an Apple watch product would likely include sensors that could pair with health related applications (over low energy bluetooth) to the users iPhone.

Apple duly recruited Angela Ahrendts, previously CEO of Burberry, to head up Apple’s Retail Operations. Shortly followed by Nike Fuelband Consultant Jay Blahnik and several Medical technology hires. Nike (where Apple CEO Tim Cook is a Director) laid off it’s Fuelband hardware team, citing a future focus on software only. And just this weekend, it was announced that Apple had recruited the Tag Heuer Watches VP of Sales (here).

That article on the Verge had a video of an interview from CNBC with Jean-Claude Biver, who is Head of Watch brands for LVMH – including Louis Vuitton, Hennessey and TAG Heuer. The bizarre thing (to me) he mentioned was that his employee who’d just left for a contract at Apple was not going to a Direct Competitor, and that he wished him well. He also cited a “Made in Switzerland” marketing asset as being something Apple could then leverage. I sincerely think he’s not naive, as Apple may well impact his market quite significantly if there was a significant product overlap. I sort of suspect that his reaction was that of someone partnering Apple in the near future, not of someone waiting for an inbound tidal wave from an foreign competitor.

Google, at their I/O Developers Conference last week, duly announced Android Wear, among which was support for Smart Watches from Samsung, LG and Motorola. Besides normal time and date use, include the ability to receive the excellent “Google Now” notifications from the users phone handset, plus process email. The core hope is that application developers will start to write their own applications to use this new set of hardware devices.

Two thoughts come to mind.

A couple of weeks back, my wife needed a new battery in one of her Swatch watches. With that, we visited the Swatch Shop outside the Arndale Centre in Manchester. While her battery was being replaced, I looked at all the displays, and indeed at least three range catalogues. Beautiful fashionable devices that convey status and personal expression. Jane duly decided to buy another Swatch that matched an evening outfit likely to be worn to an upcoming family Wedding Anniversary. A watch battery replacement turned into an £85 new sale!

Thought #1 is that the Samsung and LG watches are, not to put a finer point on it, far from fashion items (I nearly said “ugly”). Available in around 5 variations, which map to the same base unit shape and different colour wrist bands. LG likewise. The Moto 360 is better looking (bulky and circular). That said, it’s typically Fashion/Status industry suicide with an offer like this. Bill Geiser related that “one size fits all” is a dangerous strategy; suppliers typically build a common “watch movement” platform, but wrap this in an assortment of enclosures to appeal to a broad audience.

My brain sort of locks on to a possibility, given a complete absence of conventional watch manufacturers involved with Google’s work, to wonder if Apple are OEM’ing (or licensing) a “watch guts” platform usable by Watch manufacturers to use in their own enclosures.

Thought #2 relates to sensors. There are often cited assumptions that Apple’s iWatch will provide a series of sensors to feed user activity and vital signs into their iPhone based Health application. On that assumption, i’ve been noting the sort of sensors required to feed the measures maintained “out of the box” by their iPhone health app, and agonising as to if these would fit on a single wrist based device.

The main one that has been bugging me – and which would solve a need for millions of users – is that of measuring glucose levels in the bloodstream of people with Diabetes. This is usually collected today with invasive blood sampling; I suspect little demand for a watch that vampire bites the users wrist. I found today that there are devices that can measure blood glucose levels by shining Infrared Light at a skin surface using near-infrared absorption spectroscopy. One such article here.

The main gotcha is that the primary areas where such readings a best taken are on the ear drum or on the inside of an arm’s elbow joint. Neither the ideal position for a watch, but well within the reach of earbuds or a separate sensor. Both could communicate with the Health App directly wired to an iPhone or over a low energy bluetooth connection.

Blood pressure may also need such an external sensor. There are, of course, plenty of sensors that may find their way into a watch style form factor, and indeed there are Apple patents that discuss some typical ones they can sense from a wrist-attached device. That said, you’re working against limited real estate for the devices electronics, display and indeed the size of battery needed to power it’s operation.

In summary, I wonder aloud if Apple are providing an OEM watch movement for use by conventional Watch suppliers, and whether the Health sensor characteristics are better served by a raft of third party, low energy bluetooth devices rather than an iWatch itself.

About the only sure thing is that when Apple do finally announce their iWatch, that my wife will expect me to be early in the queue to buy hers. And that I won’t disappoint her. Until then, iWatch rumours updated here.

The Internet of Things withers – while HealthKit ratchets along

ianwaring Apple, Cars, Fitness, Google, Gym, HomeKit, iBeacon, Kickstarter, Low Energy Bluetooth, Medical, Mobiles, Software, Watches Leave a comment

FDA Approved Logo

I sometimes shudder at the estimates, as once outlined by executives at Cisco, that reckons the market for “Internet of Things” – communicating sensors embedded everywhere – would be likely be a $19 trillion market. A market is normally people willing to invest to make money, save money, to improve convenience or reduce waste. Or a mix. I then look at various analysts reports where they size both the future – and the current market size. I really can’t work out how they arrive at today’s estimated monetary amounts, let alone do the leap of faith into the future stellar revenue numbers. Just like IBM with their alleged ‘Cloud’ volumes, it’s difficult to make out what current products are stuffed inside the current alleged volumes.

One of my sons friends is a Sales Director for a distributor of sensors. There appear good use cases in Utility networks, such as monitoring water or gas flow and to estimate where leaks are appearing, and their loss dimensions. This is apparently already well served. As are industrial applications, based on pneumatics, fluid flow and hook ups to SCADA equipment. A bit of RFID so stock movements can be automatically checked through their distribution process. Outside of these, there are the 3 usual consumer areas; that of cars, health and home equipment control – the very three areas that both Apple and Google appear to be focussed on.

To which you can probably add Low Power Bluetooth Beacons, which will allow a phone handset to know it’s precise location, even where GPS co-ordinates are not available (inside shopping centres as an example). If you’re in an open field with sight of the horizon around you in all directions, circa 14 GPS satellites should be “visible”; if your handset sees two of them, it can suss your x and y co-ordinates to a meter or so. If it sees 3 satellites, that’s normally enough to calculate your x, y and z co-ordinates – ie: geographic location and height above sea level. If it can only see 1 or none, it needs another clue. Hence a super secret rollout where vendors are offering these LEB beacons and can trade the translation from their individual identifiers to their exact location.

In Apple’s case, Apple Passbook Loyalty Cards and Boarding Passes are already getting triggered with an icon on the iOS 8 home screen when you’re adjacent to a Starbucks outlet or Virgin Atlantic Check-in desk; one icon press, and your payment card or boarding pass is there for you already. I dare say the same functionality is appearing in Google Now on Android; it can already suss when I get out of my car and start to walk, and keeps a note of my parking location – so I can ask it to navigate me back precisely. It’s also started to tell me what web sites people look at when they are in the same restaurant that i’m sitting in (normally the web site or menu of the restaurant itself).

We’re in a lull between Apple’s Worldwide Developer Conference, and next weeks equivalent Google I/O developer event, where Googles version of Health and HomeKit may well appear. Maybe further developments to link your cars Engine Control Unit to the Internet as well (currently better engaged by Phil Windley’s FUSE project). Apple appear to have done a stick and twist on connecting an iPhone to a cars audio system only, where the cars electronics use Blackberry’s QNX embedded Linux software; Android implementations from Google are more ambitious but (given long car model cycle times) likely to take longer to hit volume deployments. Unless we get an unexpected announcement at Google I/O next week.

My one surprise is that my previous blog post on Apples HomeKit got an order of magnitude more readers than my two posts on the Health app and the HealthKit API (posts here and here). I’d never expected that using your iPhone as a universal, voice controlled home lock/light/door remote would be so interesting to people. I also hear that Nest (now a Google subsidiary) are about to formally announce shipment of their 500,000th room temperature control. Not sure about their Smoke Alarm volumes to date though.

That apart, I noticed today that the US Food and Drug Administration had, in March, issued some clarifications on what type of mobile connected devices would not warrant regulatory classification as a medical device in the USA. They were:

  1. Mobile apps for providers that help track or manage patient immunizations by assessing the need for immunization, consent form, and immunization lot number

  2. Mobile apps that provide drug-drug interactions and relevant safety information (side effects, drug interactions, active ingredient) as a report based on demographic data (age, gender), clinical information (current diagnosis), and current medications

  3. Mobile apps that enable, during an encounter, a health care provider to access their patient’s personal health record (health information) that is either hosted on a web-based or other platform

So, it looks like Apple Health application and their HealthKit API have already skipped past the need for regulatory approvals there already. The only thing i’ve not managed to suss is how they measure blood pressure and glucose levels on a wearable device without being invasive. I’ve seen someone mention that a hi res camera is normally sufficient to detect pulse rates by seeing image changes on a picture of a patients wrist. I’ve also seen an inference that suitably equipped glasses can suss basic blood composition looking at what is exposed visibly in the iris of an eye. But if Apple’s iWatch – as commonly rumoured – can detect Glucose levels for Diabetes patients, i’m still agonising how they’d do it. Short of eating or attaching another (probably disposable) Low Energy Bluetooth sensor for the phone handset to collect data from.

That looks like it’ll be Q4 before we’ll all know the story. All I know right now is that Apple produce an iWatch, and indeed return the iPhone design to being more rounded like the 3S was, that my wife will expect me to be in the queue on release date to buy them both for her.

An initial dive into Apples new Health App (and HealthKit API)

ianwaring Apple, Fitness, Gym, Medical Leave a comment

Apple HealthKit Icon

Apple announced their new Health application (previously known during rumours as HealthBook) and the associated HealthKit Application Programming Interface (API) at their Worldwide Developers Conference earlier this week. A video of the associated conference presentation that focussed exclusively on it at WWDC was put up yesterday, and another that preceded it – showing how you interface low energy Bluetooth sensors to an iPhone and hence to feed it – should be up shortly.

Even though the application won’t be here until iOS 8 releases (sometime in the Autumn), the marketing folks have already started citing the already frequent use of iPhones in Health and Fitness applications here (the campaign title is “Strength” and the video lasts for exactly one minute).

Initial discoveries:

  1. The application is iPhone only. No iPad version at first release (if ever).
  2. A lot of the set-up work for an application provider relates to the measures taken, and the associated weight/volume metrics used. These can be complex (like mg/DL, calories, steps, temperature, blood pressure readings, etc) and are stored with corresponding timestamps.
  3. The API provides a rich set of unit conversion functions (all known count, Imperial and Metric measure combinations), so these shouldn’t be needed in your application code.
  4. Access to the data is authorised by class (measure type). Apple have been really thorough on the security model; users get fine grained control on which data can be accessed by each application on the handset. Even to the extent that no-one can ask “Is this user sampling blood pressure on this device”? Apps can only ask “Are there blood pressure readings that my application has permission to access please?”. The effect is that  apps can’t tell the difference between “what isn’t sampled” or “what is sampled but denied access” to them; hence inferences that the user may have diabetes is impossible to deduce from the yes/no answer given. Well thought out security.
  5. There is provision for several devices taking duplicated readings (eg: having a FitBit step counter and the handset deducing step count itself from it’s own sensors). The API queries can be told which is the default device, so that when stats are mapped out, secondary device data can be used if and where there are gaps in the primary sensors data. I guess the use case is wearing your Fitbit out running when leaving your phone handset at home (or vice versa); if both are operating simultaneously, the data samples reported in the time slots mapped come only from the primary device.
  6. Readings are stored in one locally held Object orientated database for all measures taken, by all monitoring devices you use. All health applications on your handset use this single database, and need to be individually authorised for each class of data readings you permit them to be exposed to. No permission, no access. This is the sort of detail tabloid newspapers choose to overlook in order to get clickbait headlines; don’t believe scare stories that all your data is immediately available to health professionals or other institutions – it is patently not the case.

The end result is that you consolidate all your health related data in one place, and can selectively give access to subsets of it to other applications on your iPhone handset (and to revoke permissions at any time). The API contains a statistics functions library and the ability to graph readings against a timeline, as demonstrated by the Health Application that will be present on every iPhone running iOS 8. The side effect of this is that the iPhone is merely acting as a data collection device, and is not dishing out advice – something that would otherwise need regulatory approvals.

Vendors/users of all manner of sensors, weighing scales, Boditrax machines, monitors, etc can add support for their devices to feed data into the users Health database on the users handset. I’m just waiting for the video of the WWDC session that shows how to do this to be made available on my local copy of the WWDC app. More insights may come once I have the opportunity to hear that through.

In the meantime, Mayo Clinic have developed an application that can message a health professional if certain readings go outside safe bounds that they have set for their patient (with the patients permission!). One provider in the USA is giving the ability to feed data – with the patients permission – directly into their doctors patient database. I suspect there are a myriad of use cases that applications can be developed for; there is already quite a list of institutions piloting related applications:

Apple HealthKit Pilot Users

The one point to leave with is probably the most important of all. Health data is a valuable asset, and must be protected to avoid any exposure of the user to potential personal or financial prejudice. Apple have done a thorough piece of work to ensure that for the users of their handsets.

The reward is likely to be that an iPhone will cement itself even further into the daily lives of it’s owners just as they have to date – and without unwanted surprises.

Footnote: now i’ve listened to the associated Health App Devices Presentation from WWDC, i’ve added an extra blog post with more advanced information on the Health Apps capabilities and device support here.

12 years of data recording leads to dose of the obvious

ianwaring Fitness, Gym, Medical, Metrics, Statistics, Tableau Leave a comment

Ian Waring Weight Loss Trend Scatter Graph

As mentioned yesterday, I finally got Tableau Desktop Professional (my favourite Analytics software) running on Amazon Workspaces – deployed for all of $35 for the month instead of having to buy my own Windows PC. With that, a final set of trends to establish what I do right when I consistently lose 2lbs/week, based on an analysis of my intake (Cals, Protein, Carbs and Fat) and Exercise since June 2002.

I marked out a custom field that reflected the date ranges on my historical weight graph where I appeared to consistently lose, gain or flatline. I then threw all sorts of scatter plots (like the one above, plotting my intake in long periods where I had consistent weight losses) to ascertain what factors drove the weight changes i’ve seen in the past. This to nominally to settle on a strategy going forward to drop to my target weight as fast as I could in a sustainable fashion. Historically, this has been 2lbs/week.

My protein intake had zero effect. Carbs and Fat did, albeit they tracked the effect of my overall Calorie intake (whether in weight or in the number of Calories present in each – 1g of Carbs = 3.75 Kcals, and 1g of Fat = 9 Kcals; 1g of Protein is circa 4 Kcals). The WeightLossResources recommended split of Kcals from the mix to give an optimum balance in their view (they give a daily pie-chart of Kcals from each) is 50% Carbs, 30% Fat and 20% Protein.

So, what are the take-homes having done all the analysis?

Breathtakingly simple. If I keep my food intake, less exercise calories, at circa 2300-2350 calories per day, I will lose a consistent 2lbs. The exact balance between carbs, protein and fat intake doesn’t matter too materially, as long as the total is close, though my best every long term loss had me running things close to the recommended balance. All eyes on that pie chart on the WLR web site as I enter my food then!

The stupid thing is that my current BMR (Basal Metabolic Rate is the minimum level of energy your body needs when at rest to function effectively including your respiratory and circulatory organs, neural system, liver, kidneys, and other organs) is 2,364, and before the last 12 week Boditrax competition at my gym, it was circa 2,334 or so. Increased muscle through lifting some weights put this up a little.

So, the basic message is to keep what I eat down to the same calorie value, less the calories from any exercise, down to the same level as my BMR, which in turn will track down as weight goes. That sort of guarantees that any exercise I take over and above what I log – which is only long walks with Jane and gym exercise – will come off my fat reserves.

Simple. So, all else being equal, put less food in my mouth, and i’ll lose weight. The main benefit of 12 years of logging my intake is I can say authoritatively – for me – the levels at which this is demonstrably true. And that should speed my arrival at my optimum weight.

New Learnings, 12 week Boditrax Challenge, still need Tableau

ianwaring Fitness, Google, Gym, Medical, Statistics, Tableau, Training Leave a comment

The Barn Fitness Club Cholsey

One of the wonderful assets at my excellent local gym – The Barn Fitness Club in Cholsey – is that they have a Boditrax machine. This looks like a pair of bathroom scales with metal plates where you put your feet, hooked up to a PC. It bounces a small charge through one foot and measures the signal that comes back through the other. Measuring your weight at the same time and having previously been told your age, it can then work out the composition of your body in terms of fat, muscle, water and bone. The results are dropped on the Boditrax web site, where you can monitor your progress.

For the last 12 weeks, the gym has run a 12 week Boditrax challenge. Fortunately, I pay James Fletcher for a monthly Personal Training session there, where he takes readings using this machine and adjusts my 3x per week gym routine accordingly. The end results after 12 weeks have been (top  graph my weight progress, the bottom my composition changes):

Boditrax Challenge Ian W Weight Tracking

Boditrax Challenge Ian W Final Results

The one difference from previous weight loss programmes i’ve followed is the amount of weight work i’d been given this time around. I used to be always warned that muscle weighs considerably more than fat, so to try to keep to cardio work to minimise both. The thinking these days appears to be to increase your muscle mass a little, which increases your metabolic rate – to burn more calories, even at standstill.

The one thing i’ve done since June 3rd 2002 is to tap my food intake and exercise daily into the excellent Weight Loss Resources web site. Hence I have a 12 year history of exact figures for fat, carbs and protein intake, weight and corresponding weight changes throughout. I used these in a recent Google Course on “Making sense of Data”, which used Google Fusion tables, trying to spot what factors led to a consistent 2lbs/week weight loss.

There are still elements of the storyboard I still need to fit in to complete the picture, as Fusion Tables can draw a scatter plot okay, but can’t throw a weighted trend line through that cloud of data points. This would give me a set of definitive stories to recite; what appears so far is that I make sustainable 2lbs/week losses below a specific daily calorie value if I keep my carbs intake down at a specific level at the same time. At the moment, i’m tracking at around 1lb/week, which is half the rate I managed back in 2002-3 – so i’m keen to expose the exact numbers I need to follow. Too much, no loss; too little, body goes into a siege mentality – and hence the need for a happy medium.

I tried to get a final fix on the exact nett intake and carb levels in Google Spreadsheets, which isn’t so adept at picking data subsets with filters – so you end up having the create a spreadsheet for each “I wonder if” question. So, i’ve largely given up on that until I can get my mits on a Mac version of Tableau Desktop Professional, or can rent a Windows Virtual Desktop on AWS for $30 for 30 days to do the same on it’s Windows version. Until then, I can see the general picture, but there are probably many data points from my 3,800+ weeks of sampled data that plot on top of each other – hence the need for the weighted trend line in order to expose the definitive truth.

The nice thing about the Boditrax machine is that it knows your Muscle and Fat composition, so can give you an accurate reading for your BMR – your Basal Metabolic Rate. This is the minimum level of energy your body needs when at rest to function effectively including your respiratory and circulatory organs, neural system, liver, kidneys, and other organs. This is typically circa 70% of your daily calorie intake, the balance used to power you along.

My BMR according to the standard calculation method (which assumes a ‘typical’ %muscle content) runs about 30 kcals under what Boditrax says it actually is. So, I burn an additional 30 Kcals/day due to my increased muscle composition since James Fletchers training went into place.

Still a long way to go, but heading in the correct direction. All I need now is that copy of Tableau Desktop Professional so that I can work out the optimum levels of calorie and carbs intake to maximise the long term, relentless loss – and to ensure I track at those levels. In the meantime, i’ll use the best case I can work out from visual inspection of the scatter plots.

I thoroughly recommend the Barn Fitness Club in Cholsey, use of their Boditrax machine and regular air time with any of their Personal Trainers. The Boditrax is only £5/reading (normally every two weeks) and an excellent aid to help achieve your fitness goals.

Just waiting to hear the final result of the 12 week Boditrax challenge at the Club – and to hope i’ve done enough to avoid getting the wooden spoon!

Boditrax Challenge Home Page

 

In the meantime, it’s notable that my approx nett calorie intake level (calories eaten less exercise calories) to lose 2lbs/week appears to be my current BMR – which sort of suggests the usual routine daily activity I don’t log (walking around the home, work or shops) is sufficient to hit the fat reserves. An hour of time with Tableau on my data should be enough to confirm if that is demonstrably the case, and the level of carbs I need to keep to in order to make 2lbs/week a relentless loss trend again.