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Multi-day Longitudinal Assessment of Physical Activity and Sleep Behavior Among Healthy Young and Older Adults Using Wearable Sensors - 23/10/19

Doi : 10.1016/j.irbm.2019.10.002 
R. Soangra a, b
a Department of Physical Therapy, Crean College of Health and Behavioral Sciences, Chapman University, Irvine, CA 92618, USA 
b Department of Electrical Engineering and Computer Science, Fowler School of Engineering, Orange CA, 92866, USA 

Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Wednesday 23 October 2019
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Abstract

Objectives

The number of elderly people is growing rapidly and aging is found to affect activities of daily living. Older adults are found to perform less physical activity when compared to younger ones. In the perspective of movement behavior, it is not well understood how are elderly different from younger ones. It is not known whether they produce only low frequency movement accelerations or the overall number of movements produced are reduced in elderly. It is also not known how elderly and younger ones perform movement transitions throughout the duration of a day and during night-time sleep.

Material and methods

In this study, 10 healthy young and 10 healthy old participants wore inertial measurement unit at their lower back for 3-days. The 24 hours of day were divided into four 6 hour time zones and transitions made by young and elderly were investigated. All participants performed their regular daily activities unhindered and longitudinal multi-day signals for acceleration and angular velocity were analyzed. Time-frequency analysis was performed using wavelet transform and frequency content of each movement performed was computed.

Results

We found that both young and older adults performed significantly more low amplitude movements than medium and high amplitude movements. Healthy young adults produced significantly more movements at 1.1 Hz than older adults. Healthy young adults were also found to have produced significantly smaller number of transitions in the mid-phases of sleep. They were also found to produce significantly larger accelerations during night-time sleep transitions than their older counterparts.

Conclusion

The advantages of collecting longitudinal data about human movement and sleep transition data can lead us to important clinical diagnosis. The information from longitudinal assessment can help develop lifestyle interventions for disease prevention, monitoring of chronic diseases to prevent or slow disease progression among elderly people.

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Graphical abstract

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Highlights

Aging affects activities of daily living in human beings.
Low frequency movements are performed among young and older adults.
Young adults produced significantly more movements at 1.1 Hz.
At night, young produced significantly larger accelerations during transitions.
Activity profiling may detect intervention effects or disease progression.

Le texte complet de cet article est disponible en PDF.

Keywords : Wearable sensors, Longitudinal monitoring, Activities of daily living, Inertial measurement units


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