Contact-free radar recordings of body movement can reflect ultradian dynamics of sleep
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Contact-free radar recordings of body movement can reflect ultradian dynamics of sleep. / Heglum, Hanne Siri Amdahl; Drews, Henning Johannes; Kallestad, Havard; Vethe, Daniel; Langsrud, Knut; Sand, Trond; Engstrom, Morten.
I: Journal of Sleep Research, Bind 31, Nr. 6, 13687, 2022.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Contact-free radar recordings of body movement can reflect ultradian dynamics of sleep
AU - Heglum, Hanne Siri Amdahl
AU - Drews, Henning Johannes
AU - Kallestad, Havard
AU - Vethe, Daniel
AU - Langsrud, Knut
AU - Sand, Trond
AU - Engstrom, Morten
PY - 2022
Y1 - 2022
N2 - This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as Locomotor Inactivity During Sleep (LIDS). LIDS was designed as a simple transformation of actigraphy recordings of wrist movement, meant to emphasise and enhance the contrast between movement and non-movement and to reveal patterns of low residual activity during sleep that correlate with ultradian REM/NREM cycles. We adapted the LIDS transformation for a radar that detects body movements without direct contact with the subject and applied it to a dataset of simultaneous recordings with polysomnography, actigraphy, and radar from healthy young adults (n = 12, four nights of polysomnography per participant). Radar and actigraphy-derived LIDS signals were highly correlated with each other (r > 0.84), and the LIDS signals were highly correlated with reduced-resolution polysomnographic hypnograms (r(radars) >0.80, r(actigraph) >0.76). Single-harmonic cosine models were fitted to LIDS signals and hypnograms; significant differences were not found between their amplitude, period, and phase parameters. Mixed model analysis revealed similar slopes of decline per cycle for radar-LIDS, actigraphy-LIDS, and hypnograms. Our results indicate that the LIDS technique can be adapted to work with contact-free radar measurements of body movement; it may also be generalisable to data from other body movement sensors. This novel metric could aid in improving sleep monitoring in clinical and real-life settings, by providing a simple and transparent way to study ultradian dynamics of sleep using nothing more than easily obtainable movement data.
AB - This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as Locomotor Inactivity During Sleep (LIDS). LIDS was designed as a simple transformation of actigraphy recordings of wrist movement, meant to emphasise and enhance the contrast between movement and non-movement and to reveal patterns of low residual activity during sleep that correlate with ultradian REM/NREM cycles. We adapted the LIDS transformation for a radar that detects body movements without direct contact with the subject and applied it to a dataset of simultaneous recordings with polysomnography, actigraphy, and radar from healthy young adults (n = 12, four nights of polysomnography per participant). Radar and actigraphy-derived LIDS signals were highly correlated with each other (r > 0.84), and the LIDS signals were highly correlated with reduced-resolution polysomnographic hypnograms (r(radars) >0.80, r(actigraph) >0.76). Single-harmonic cosine models were fitted to LIDS signals and hypnograms; significant differences were not found between their amplitude, period, and phase parameters. Mixed model analysis revealed similar slopes of decline per cycle for radar-LIDS, actigraphy-LIDS, and hypnograms. Our results indicate that the LIDS technique can be adapted to work with contact-free radar measurements of body movement; it may also be generalisable to data from other body movement sensors. This novel metric could aid in improving sleep monitoring in clinical and real-life settings, by providing a simple and transparent way to study ultradian dynamics of sleep using nothing more than easily obtainable movement data.
KW - actigraphy
KW - LIDS
KW - REM
KW - NREM cycles
KW - sleep monitoring
KW - UWB radar
KW - ACTIGRAPHY
KW - MEDICINE
U2 - 10.1111/jsr.13687
DO - 10.1111/jsr.13687
M3 - Journal article
C2 - 35794011
VL - 31
JO - Journal of Sleep Research
JF - Journal of Sleep Research
SN - 1365-2869
IS - 6
M1 - 13687
ER -
ID: 314622999