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Dr Dean J Miller

@drdeanjmiller.bsky.social

Sleep Scientist | Senior Lecturer

173 Followers  |  75 Following  |  117 Posts  |  Joined: 21.11.2024  |  2.2914

Latest posts by drdeanjmiller.bsky.social on Bluesky

Have a gander at my new piece in the Conversation!

25.06.2025 23:00 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Have you ever been told to β€œgo and touch some grass”?

In this piece, myself and Charlotte Gupta (notoriously grounded individuals πŸ‘€ ) discuss the science behind grounding.

Link below πŸ‘‡

14.05.2025 05:53 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

@aunz.theconversation.com

14.05.2025 05:51 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

This was one of the most enjoyable protocols we've run at CQUniversity's Appleton Institute, and the team involved continues to set the bar for rigorous research in sleep and nutrition.

23.02.2025 23:13 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

We investigated whether a nutritional intervention containing ingredients that may influence sleep (e.g., tryptophan) could improve subjective or objective sleep in healthy young males. The results? No significant effectsβ€”but an important reminder that null findings still provide valuable insights!

23.02.2025 23:13 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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‼️NEW RESEARCH‼️

Excited to share our latest paper led by Dr. Matthew Morrison!

journals.humankinetics.com/view/journal...

23.02.2025 23:13 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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If you were going to run 100 miles (161 km), would you stop to sleep? Or push through?

Find out the most common approaches to sleep during ultra-marathons, and our thoughts on future strategies in our open access paper.

mdpi.com/1720578

@academic-chatter.bsky.social @phdvoice.bsky.social

05.12.2024 02:06 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0

@phdsleepy.bsky.social

03.12.2024 00:20 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Great to hear! A balanced consideration of personal preference, context, and limitations of technology is the best practical way forward - imho.

29.11.2024 23:14 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
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Validity and reliability of the Oura Ring Generation 3 (Gen3) with Oura sleep staging algorithm 2.0 (OSSA 2.0) when compared to multi-night ambulatory polysomnography: A validation study of 96 partici... To evaluate the validity and the reliability of the Oura Ring Generation 3 (Gen3) with Oura Sleep Staging Algorithm 2.0 (OSSA 2.0) through multi-night…

www.sciencedirect.com/science/arti...

29.11.2024 08:02 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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Accuracy of Three Commercial Wearable Devices for Sleep Tracking in Healthy Adults Sleep tracking by consumers is becoming increasingly prevalent; yet, few studies have evaluated the accuracy of such devices. We sought to evaluate the accuracy of three devices (Oura Ring Gen3, Fitbi...

There are also more recent validations from other teams below!

www.mdpi.com/1424-8220/24...

29.11.2024 08:02 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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A Validation of Six Wearable Devices for Estimating Sleep, Heart Rate and Heart Rate Variability in Healthy Adults The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 a...

Please have a read of the paper and send through any thoughts, questions, or critiques!
#appletonpublications #academicchatter #academicpapers #sleeppeeps #sportscience www.mdpi.com/1424-8220/22...

29.11.2024 08:02 β€” πŸ‘ 5    πŸ” 0    πŸ’¬ 2    πŸ“Œ 0
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HRV: Again, the way in which HRV was sampled differed across the devices (please read paper for context). The devices ranged from low relative agreement to almost perfect relative agreement with ECG (Bland Altman plots below).

29.11.2024 08:02 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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HR : The way in which HR was sampled differed across the devices (again please read paper for context). The devices ranged from moderate relative agreement to almost perfect relative agreement with ECG (Bland Altman plots below).

29.11.2024 08:02 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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All devices are are valid for field-based assessment of the timing and duration of sleep. While all can improve their assessment of sleep stage, better performing devices may provide valuable information when monitoring for sustained, meaningful changes in sleep stage.

29.11.2024 08:02 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

All devices detected >90% of sleep, but Polar, Oura Gen 2, WHOOP 3.0 and Somfit outperformed Apple Watch and Garmin for detecting wake. The devices ranged from 50 to 65% agreement for multi-state sleep when compared to PSG. But what does this mean?

29.11.2024 08:02 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

The wearable devices were: Apple Watch S6, Garmin F'runner 245 Music, Polar Vantage V, Oura Ring G2, WHOOP 3.0, and Somfit.Records from each device (see paper for specific data extraction) were lined up with PSG-derived and ECG-derived data.

29.11.2024 08:02 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

In collaboration with The Australian Institute of Sport, we recruited 53 participants to spend 1 night in the Appleton Institute Sleep Lab. Participants spent 9h in bed wearing 6 devices, as well as gold standard polysomnography (PSG; sleep) and electrocardiogram (ECG; heart rate).

29.11.2024 08:02 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Caveat: more detail than can be condensed into a thread is required to fully understand such validations. Please use this thread as a primer for digesting the full paper!

29.11.2024 08:02 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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A Validation of Six Wearable Devices for Estimating Sleep, Heart Rate and Heart Rate Variability in Healthy Adults The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 a...

🚨If you (1) sleep; and (2) wear a device that measures sleep/heart rate/ heart rate variability. Here is a thread explaining (briefly) our recent validation of 6 commonly used wearables🧡

doi.org/10.3390/s221...

29.11.2024 08:02 β€” πŸ‘ 10    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0

#sleep #sleepscience #sleepmedicine #medicine

27.11.2024 06:52 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
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Such a great chat with my childhood mate, former teammate, and now Emergency Physician Dr Akash Patel.

shorturl.at/RHOMB

27.11.2024 06:51 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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a man in a green sweater is standing in front of a television with the words im in written on his chest . ALT: a man in a green sweater is standing in front of a television with the words im in written on his chest .
27.11.2024 05:25 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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The effect of alcohol on subsequent sleep in healthy adults: A systematic review and meta-analysis Alcohol is commonly consumed prior to bedtime with the belief that it facilitates sleep. This systematic review and meta-analysis investigated the imp…

🚨 NEW PAPER 🚨

Have you ever noticed how alcohol impacts your sleep?

Our new paper, led by Dr Carissa Gardiner is now available as an online pre proof.

#sleep #sleepscience #alcohol

www.sciencedirect.com/science/arti...

21.11.2024 10:32 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Sleep scientist here πŸ‘‹ always happy to chat sleep 😴

21.11.2024 09:16 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

G’day, I’m a sleep scientist from Australia. If you like to sleep, then follow me. 🀣 #scientist #sleep

21.11.2024 09:12 β€” πŸ‘ 3    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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Dr Dean J Miller | Sleep & Performance Scientist on Instagram: "Our latest study looked at sleep/wake behaviour during a 200 mile Ultra-Marathon. Despite the low sample size, these findings are helpful for athletes due the scarcity of objectively measured sleep during these highly challenging races. β €β €β €β €β €β €β €β €β € Darren Bianchi, our superstar honours student did a great job collecting the data and putting together his first publication. More to come! πŸ‘€ β €β €β €β €β €β €β €β €β € Please have a read using the DOI below or using the link in my stories!" 44 likes, 10 comments - drdeanjmiller on March 6, 2022: "Our latest study looked at sleep/wake behaviour during a 200 mile Ultra-Marathon. Despite the low sample size, these findings are helpful for athletes due the scarcity of objectively measured sleep during these highly challenging races. β €β €β €β €β €β €β €β €β € Darren Bianchi, our superstar honours student did a great job collecting the data and putting together his first publication. More to come! πŸ‘€ β €β €β €β €β €β €β €β €β € Please have a read using the DOI below or using the link in my stories!".

More here: πŸ‘‡πŸ‘‡πŸ‘‡

x.com/EJIHPE_MDPI/st… instagram.com/reel/CayZWnMA4…

16.01.2023 22:45 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
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Evaluating the Typical Day-to-Day Variability of WHOOP-Derived Heart Rate Variability in Olympic Water Polo Athletes Heart rate (HR) and HR variability (HRV) can be used to infer readiness to perform exercise in athletic populations. Advancements in the photoplethysmography technology of wearable devices such as WHOOP allow for the frequent and convenient measurement of HR and HRV, and therefore enhanced application in athletes. However, it is important that the reliability of such technology is acceptable prior to its application in practical settings. Eleven elite male water polo players (age 28.8 Β± 5.3 years [mean Β± standard deviation]; height 190.3 Β± 3.8 cm; body mass 95.0 Β± 6.9 kg; international matches 117.9 Β± 92.1) collected their HR and HRV daily via a WHOOP strap (WHOOP 3.0, CB Rank, Boston, MA, USA) over 16 weeks ahead of the 2021 Tokyo Olympic Games. The WHOOP strap quantified HR and HRV via wrist-based photoplethysmography during overnight sleep periods. The weekly (i.e., 7-day) coefficient of variation in lnRMSSD (lnRMSSDCV) and HR (HRCV) was calculated as a measure of day-to-day variability in lnRMSSD and HR, and presented as a mean of the entire recording period. The mean weekly lnRMSSDCV and HRCV over the 16-week period was 5.4 Β± 0.7% (mean Β± 95% confidence intervals) and 7.6 Β± 1.3%, respectively. The day-to-day variability in WHOOP-derived lnRMSSD and HR is within or below the range of day-to-day variability in alternative lnRMSSD (~3–13%) and HR (~10–11%) assessment protocols, indicating that the assessment of HR and HRV by WHOOP does not introduce any more variability than that which is naturally present in these variables.



mdpi.com/1424-8220/22/1…

26.09.2022 02:58 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Overall, this means that WHOOP 3.0-derived HR and HRV are acceptable for inferring readiness to perform exercise among athletes. Sport and exercise science practitioners may confidently use @WHOOP HR and HRV in practical settings.

26.09.2022 02:57 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

The typical day-to-day variability in WHOOP 3.0-derived HRV was comparable to commonly utilised recording devices and scientific protocols, regardless of training load (please see discussion for specific ranges).

26.09.2022 02:57 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

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