Wearable technology refers to devices that can be worn on the body - such as watches, straps, patches and/or rings. These devices collect physiological data to provide insights about health and performance in training, competition, recovery and sleep.

With advancement in technologies, wearables are being used more and more by elite athletes to quantify and track their progress on a daily basis.

What do wearables measure?

How do wearables measure human performance?

How accurate are wearables?

How are athletes using wearables?

“I want to track my sleep”

If you are interested in tracking your sleep with a wearable, it is important to monitor for sustained, meaningful changes in sleep/wake behaviour.

Most wearables use automatic detection of sleep to initiate sleep data collection. Unless you are particularly concerned about how long it is taking you to fall asleep, you can use this automatic function, but monitor the following:

1. Check whether the sleep/wake times line up with when you went to bed and when you woke up. If the results seem incorrect (e.g., sleep time is 1 hour before you attempted to sleep), manually adjust the sleep period to reflect the correct timing. Such misestimations may be due to wearable placement, or pre-sleep behaviour (e.g., watching a movie in bed).
2. Even though wearables are improving their ability to measure sleep stage, place more importance on tracking sleep timing (try keep consistent where possible) and total sleep.
3. If sleep/wake timing and total sleep time show meaningful changes over a sustained period of time (and data appear to line up with your behaviours), seek advice from your support team.

If you are interested in tracking your sleep with a wearable.

“I am struggling to fall asleep”

If you think you are struggling to fall asleep at night and want to use a wearable to confirm this, the variable of interest is sleep onset latency (i.e., time between attempting to sleep and falling asleep).

Most wearables automatically detect sleep (i.e., you do not have to input bed and wake times). However, wearables are automatically likely detecting the start of sleep – not the time taken to fall asleep. So, to gain a more accurate estimation of sleep onset latency you should either:

1. Manually “start” a sleep activity in the associated smart phone app when you are attempting to sleep (i.e., when you close your eyes, not when you get into bed).
2. Note the time in which you are attempting to sleep and manually adjust the sleep times within the associated smart phone application after the sleep period.

This will provide a start time, or “anchor”, for when you begin attempting to sleep, providing a more accurate estimate of sleep onset latency.

If you think you are struggling to fall asleep at night and want to use a wearable to confirm this.

“I want to track HR and HRV”

If you are interested in tracking your heart rate and heart rate variability with a wearable, it is important to monitor for sustained, meaningful changes.

Most wearables automatically sample heart rate and heart rate variability during sleep. Consider these pointers when tracking these metrics sampled during sleep:

1. Ensure that the sleep times are accurate (i.e., adjust bed or wake time if they do not align with your behaviour). This ensures that your HR and HRV data is sampled correctly.
2. There are several factors that may impact day-to-day changes in resting heart rate or heart rate variability. Work with your support staff to monitor for sustained changes in these metrics.
3. If your device does collect data during a manual “HRV test”, ensure you are consistent in your method and try to conduct the test at the same time of day.

If you are interested in tracking your heart rate and heart rate variability with a wearable.

“I want to track 'recovery' metrics”

Several wearables provide “recovery” metrics based on combinations of other metrics (e.g., sleep, heart rate, heart rate variability). These are hard to validate, given that they are based on private algorithms made by each wearable company. If you would like to track recovery metrics, consider the following:

1. If there are sustained changes in your recovery, refer to the raw metrics (i.e., sleep, HRV) to see if any changes coincide.
2. Several of these metrics provide a score out of 100, indicating how recovered your body may be. Lower scores do not mean that you will not be able to perform that day. Pay attention to recovery practices that have positive impacts on next-day recovery scores, rather than worrying about performance impacts.

Several wearables provide “recovery” metrics based on combinations of other metrics.

Research team

The Australian Institute of Sport and Central Queensland University have partnered to provide the National High Performance Sports System with evidence-based information on wearable technologies.

Greg Roach

Professor, Appleton Institute for Behavioural Science.

Greg is a Research Professor at the Appleton Institute for Behavioural Science. Greg did his undergraduate studies at the University of Adelaide, then completed his PhD – examining the disruption caused by night work and transmeridian travel – at the University of South Australia. Since completing his PhD, Greg has worked in research-intensive positions – initially at the University of South Australia and now at CQUniversity. Greg’s research is targeted toward making discoveries about the human sleep/wake and circadian systems that can be translated into improved policy and practice to improve health, safety, and productivity.

Greg has conducted projects in the sleep laboratory, in high-fidelity road, rail, and flight simulators, and in the elite sports, long-haul transportation, mining, and healthcare industries.

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Charli Sargent

Associate Professor, Appleton Institute for Behavioural Science.

Charli is an Associate Professor at the Appleton Institute for Behavioural Science. Charli graduated with a PhD in exercise physiology in 2006 from the University of Adelaide. Since that time, Charli has pursued two major areas of research: (i) laboratory-based studies examining the impact of sleep loss and/or irregular sleep patterns on health, fatigue, exercise performance, and cognitive function, and (ii) field-based studies examining the sleep/wake behaviours of elite athletes during training and competition.

Charli has served as an editor and organiser for international scientific journals and conferences, she has taught research methods courses for undergraduate students, and she provides supervision for Honours, Masters, and PhD students in the areas of psychology and physiology.

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Dean Miller

PhD Candidate at the Appleton Institute of Behavioural Science.

Dean Miller is a Research Officer and PhD Candidate at the Appleton Institute of Behavioural Science. Dean completed his undergraduate degree in Psychological Science and Exercise Science at the University of Adelaide. Since then Dean has been completing his PhD – examining how to measure, monitor and manage the sleep of athletes.

Dean’s has conducted research examining (1) the impact of exercise timing on sleep, (2) jet lag countermeasures for athletes, (3) the validity and implementation of wearable sleep devices. As a Research Officer, Dean’s primary role is to conduct laboratory studies related to the WHOOP strap, a wearable device capable of measuring sleep and other physiological measures

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