Buyers Guide: Heart rate monitors

Points to consider

In a previous buyers guide, we have looked at some important points to consider when choosing a suitable actigraph for scientific research.

Today, however, we will focus on another substantial player in the wearable field, namely the ambulatory heart rate monitor

As traditional heart rate (HR) monitors are quite bulky and often feature many cables, they are not very suitable for measuring patients in their daily life settings. Hence, measurements taken with such devices often lack ecological validity (although their complexity does potentially offer better data quality; good enough for cardiologists to diagnose all but the most outlandish cardiac arrhythmias).

Ambulatory heart rate monitors sacrifice some of the detail of hospital-grade HR devices for to make them wearable under daily life settings. Thus facilitating the development of early warning systems for cardiac problems, or ambulatory collection of heart rate data.

If you are looking to use such mobile heart rate monitor in your own study, the following points might be worthwile to consider:

Same goal, different solutions

First things first, while your goal might be to simple measure HR, or perhaps more precisely, to collect series of Interbeat-Intervals (IBI’s), there are multiple ways to do so.  

Two common methods are Electrocardiography (ECG), and Photoplethysmography (PPG). In short, ECG measures the electrical activity of the heart, while PPG optically measures blood volume change. Both can be used to derive HR and IBI series, but do so in a different manner, which can have important consequences for your study.

Example of an ambulatory ECG monitor (the Cortrium C3).

Example of an ambulatory PPG monitor (the Ithelete finger sensor).

Moreover the data obtained with both device look very different. As ECG is based on electrical pulses, its signal shows very sharp and distinct r-peaks. As PPG measures blood volume change, its data shows much broader peaks. Also, because PPG is often measured at the extremities (fingers, earlobes), there is often a delay before the pulse is registered when compared to whose electrical signal travels much faster. 

ECG signal obtained with the Cortrium C3.

PPG signal obtained with the Ithlete finger sensor.

Better user comfort, better results

Depending on the design of your study, the time participants have to wear the HR monitor will differ. Some will opt for continuous 24 hour measurements, while others might want to measure participants for longer periods of time, possibly months.

While short term continuous measurements are very feasible and common, long term continuous measurements are often not feasible, for a number of reasons. For example, ECG measurements require the HR monitor to be attached to the chest of the participant with electrodes. The glue of these electrodes will cause skin irritations when used over longer periods of time, causing low participant compliance.

Skin irritation caused by ECG electrodes. 

ESM Item Repository

Improving Transparency in Science: ESM Item Repository

ESM stands for Ecological Sampling Method – think of it as a tool for following the development of your mood over the day. Such as filling in a mood diary 5 times a day, but then on your smartphone. ESM is currently enjoying clinical and academic interest as it enables users to monitor mood intensively in an ecological valid environment.

However, the current infrastructure for systematically categorising and storing ESM questions – or items – is a hot mess; because there is no such infrastructure in place yet!

As you could imagine, having a plethora of scientists around the world creating, translating, and editing ESM items without proper infrastructure will hinder transparency and reproducibility. Especially as a clear overview of these items, their history of use and edits, is not systematically documented anywhere.

Hence, an inspiring team of researchers from the KU Leuven, and myself, have started the ESM Item Repository – an online database for ESM items.

ESM items can be easily accessed through an online portal. If you want to find out more, or perhaps even help adding items to the repository, check out our OSF page! More interested in the code? Check out our accompanying Github page here.

ACTman: Automatic Event marker to Sleep log Functionality

Expanding ACTman's possibilities

Hi guys, I am excited to present to you here, our newest update for our ACTman package!

As you might know, we introduced the ACTman software for R as a useful tool for both preprocessing as well as analysis of actigraphy data. Hopefully ACTman will facilitate easier, quicker, and better reproducible actigraphy analyses.

A new piece of functionality we just added – and which I am very enthousiastic about – is the possibility to read in event marker files and automatically convert them to sleep logs within mere seconds!

This is an especially handy tool for those researchers who use the marker button to estimate the times of going to bed and getting out of bed. Instead of manually writting these times down, participants can just simply press the event marker.

And instead of having to manually transcribe the event marker times to a generic sleeplog, you can now have ACTman do it for you in a quick and reproducible manner!

And the best part is that you don’t have to do anything special for it. 

If you are using the MotionWatch 8, and ACTman detects no sleeplog in your working directory but does detect a marker file, it will automatically transform it to a sleeplog for you.

You also get user control over some decisions. For example, if marker buttons are missing, ACTman offers you the choice to fill them in yourself, fill in the missing value with a mean value, or to abort the analysis.

Furthermore, ACTman automatically removes any other marker between the first and lst mrker press of that day. Multiple false presses are thus no problem for ACTman.

Interested? Check ACTman out for yourself by clicking here!

Period / Frequency Converter in R

A simple but handy tool

For some time I have been delving deeper into the interesting world of Spectral Analyses.

So far I have been delighted, as this is one of those academic techniques that is broadly applicable, and can teach you a lot about various topics.

I started using spectral analyses in the context of cardiology. However, as I learn more about it, it also teached me about music theory, higher harmonics, and color spectra. Just awesome how such differing topics can be closely linked!

However, I am rambling a bit. What I wanted to give you is this; a Period / Frequency Converter in R. When I first learned about spectral analyses I struggled a bit with the frequency and period units.  As such, I programmed this little tool to easily convert periods to frequencies and back again. Feel free to try and use it! You can find it on my Github page:

Review of the Wearables in Practice Symposium – April 6th 2018

An exciting and informative Symposium!

Friday 6th of April, finally we were heading to Soesterberg with a nice group from the University Medical Center Groningen (UMCG) to visit the “Wearables in Practice” symposium, which was organised by the Human Factors department of TNO (the Dutch Organisation for Applied Natural Scientific Research). The theme of the Symposium, Wearables in Practice, covered many of the new, smart, devices we increasingly see on the market. From smartwatch to accelerometer, and even smart alcohol meters which could help addicts, all facets of smart, wearable devices were represented here.

The day itself was organised very well, with an interesting program, and it was a lot of fun to take a look at what is happening at TNO. Also the diverse backgrounds of guests, from bussinesses to universities, and even the Royal Dutch Airforce, made it an interesting, diverse, and especially informative day. As cherry on top, I was invited to give a presentation about ACTman, a new piece of software developed by me in cooperation with scientists from the UMCG and the University of Groningen. ACTman finally allows researchers to automatically process and analyse physical activity data within mere seconds! This is especially impressive given the far longer times it took prevously to process and analyse such data, and that it cuts out a lot of the manual labour involved. As such, ACTman facillitates researchers and people interested in physical activity data in analysing large amount of activity data quickly and accurately.

 

Buyers Guide: Actigraphs

Points to consider

A common question faced by actigraphy researchers is: “Which Actigraph is most suitable for my study?”.

However, it is hard to give a simple and straightforward answer, as the optimal choice for your situation depends on your study design, e.g.,  study duration, sample characteristics, analysis goals, etc.

As such I have compiled some points which should be considered when choosing an actigraph for academic purposes:

1. Does the considered actigraph provide you with the raw data?

This is one of the most important points when considering actigraphs for academic purposes, and one of the most overlooked ones. 

“Why is this so important?”, you might ask. Well, when the raw data is not provided, the data can be somewhat akin to a black box. That is, you will have no idea what happened to the data beforehand. Perhaps the manufacturer uses a transformation on the data, or perhaps some smoothing functions. This will often be documented very sparsely, if at all.

As such, you will have at best only a partial idea of what your data respresents, possibly obfuscating your results, and your control over your own study.

Hence, when a device offers you access to the raw data you will have a better idea what happened to it and what it really means.

2. In what kind of unit will the actigraph measure?

This point is very much related to the first one. There are various units in which the actigraph can deliver its data. For example gravity units, activity ‘counts’, and manufacturer-specific units.

There are clear disadvantages with using aggregated count data, or manufacturer-specific units; they are not well suited for comparison among devices, argumentation and documentation regarding these units and their calculation could be withheld or stored behind paywalls,  the algorithms creating these counts could introduce unwanted alterations, tranformations, smoothing, or noise to the data. 

Hence, having a actigraph measure registered in a transparent, undisputed unit, which can be easily compared, and relates directly to a measurable force of nature – such as milligravity units – could prove benefical.

3. How long will the considered actigraph last before it needs new batteries?

This is an important point as battery issues can seriously hamper the quality of your dataset. Even worse, the maximum battery duration given by the manufacturer might well be an overstatement which fails to materialise under normal conditions.

In the case of one of our own studies we were once confronted with an actigraph which boasted a battery life of 4 months. As such, we designed our whole study around this period. Hence our dismay when participants returned en masse with their empty actigraphs after a mere 2 months.

Thus, we had to make an ad hoc change to our design wherein we sent participants a new actigraph near the 2 months mark. This lead to unexpected costs for sending devices, an extra burden for participants, and worst of all missing data.

Therefore, make sure you know and test the actual battery life when considering an actigraph for your study!

4. User comfort and compliance

Luckily, when compared to other physiological measurements – such as long-term ECG’s using skin irritation inducing electrodes – actigraphy is relatively benevolent. 

In my experience users can easily wear a well-designed wrist-worn actigraph for months on end without reporting any serious discomfort. 

This is a huge advantage as it thus allows for the collection of true large scale continuous datasets. This is especially important when planning complex and demanding analyses, as a lot of other measures, such as: questionnaires, daily diaries (ESM / EMA), or ECG’s, just can’t deliver enough data to conduct such complex analyses with a decent power-level.

While having participants wear an actigraph may be simple enough, having them consistently press an event marker to denote bed times and wake-up times can pose a much harder task. Such sleep logs are highly valuable in anyone interested in conducting sleep analyses.

Remember to regularly motivate and remind participants of using the event marker, or if a participant was not that consistent, you could try salvaging the sleep log by using the sleeplog_from_markers functionality from our ACTman R package which imputes missing marker presses by using the median times instead.

My Garage: Peugeot 205 GTi

Garage: Peugeot 205 GTi

Can’t forget my old love,

a raw, free-revving 1.6, in a light and nimble chassis,
really rewarding to drive hard. Pushed my limits time and time again in this baby.

Hope to drive one of these angels again..
My old Peugeot 205 1.6 GTi:

Identifying the Parts of an Alfa Romeo GTV

Parts Katalog: Alfa Romeo GTV (916; Spider)

Knowing exactly which part of your Alfa you might be working on, can save you a great deal of work . 

When working on my GTV, I frequently consult this Parts Katalog [1]. It offers plentiful visual aids in identifying the individual parts, and gives rough price estimates.

This Parts Katalog can be found on www.alfa-service.com, which offers a wide range of downloadable workshop and car documentation.

[1] GTV-Spider_(916) Katalog. (n.d.). Retrieved from https://www.alfa-service.com/modx/katalog/german/GTV-Spider_(916).pdf

Choosing the most suitable Heart Rate Monitor

Heart Rate Monitor Comparison table

Heart Rate Monitors (HRMs) can be used to monitor the condition and performance of the heart. Therefore, they are regularly considered for health-, sport-, and research purposes.

During my study into identifying transitions in depressive symptoms using Heart Rate- and Activity data, we gained some experience in the selection and operation of HRMs.

As such information might be useful for clinicians, researchers, and other people alike, I would like to share our findings with you in this HRM Comparison Table.

If you would like to discuss the selection and operation of HRMs with me, or if you would like to share your experiences with HRMs, feel free to contact me.