Wearable sensing devices for point of care diagnostics

S Mondal, N Zehra, A Choudhury… - ACS Applied Bio …, 2020 - ACS Publications
The growth of smart wearable sensing systems has gained immense importance in the
present mode of data acquisition and signaling in pharmaceutical, healthcare, and wellness …

[HTML][HTML] Recent advances in organ specific wireless bioelectronic devices: Perspective on biotelemetry and power transfer using antenna systems

AN Khan, YO Cha, H Giddens, Y Hao - Engineering, 2022 - Elsevier
The integration of electronics and biology has spawned bioelectronics and opened exciting
opportunities to fulfill the unmet needs of therapeutic treatments. Recent developments in …

Limiting racial disparities and bias for wearable devices in health science research

PJ Colvonen, PN DeYoung, NOA Bosompra… - Sleep, 2020 - academic.oup.com
Consumer wearables are devices used for tracking activity, sleep, and other health-related
outcomes (eg Apple Watch, Fitbit, Samsung, Basis, Mio, PulseOn, Whoop). Wearables …

At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch

N Zavanelli, H Kim, J Kim, R Herbert, M Mahmood… - Science …, 2021 - science.org
Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create
serious health complications when untreated; however, 80% of cases remain undiagnosed …

[HTML][HTML] Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality

H Yuan, T Plekhanova, R Walmsley, AC Reynolds… - NPJ digital …, 2024 - nature.com
Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep
stages is important in clinical studies for sleep disorder diagnoses and in the interpretation …

The future of sleep measurements: a review and perspective

ES Arnardottir, AS Islind… - Sleep medicine clinics, 2021 - sleep.theclinics.com
Sleep assessment depends both on the subjective experience of the individual and
objective measurements, which are traditionally collected through an overnight sleep study …

Ensemble computational intelligent for insomnia sleep stage detection via the sleep ECG signal

P Tripathi, MA Ansari, TK Gandhi, R Mehrotra… - IEEE …, 2022 - ieeexplore.ieee.org
Insomnia is a common sleep disorder in which patients cannot sleep properly. Accurate
detection of insomnia disorder is a crucial step for mental disease analysis in the early …

Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals

M Sharma, J Darji, M Thakrar, UR Acharya - Computers in biology and …, 2022 - Elsevier
Sleep is imperative for a healthy life as it rejuvenates memory, cognitive performance, cell
repair and eliminates waste from the muscles. Sleep-related disorders such as insomnia …

[HTML][HTML] A novel hybrid machine learning classification for the detection of bruxism patients using physiological signals

MB Bin Heyat, F Akhtar, A Khan, A Noor, B Benjdira… - Applied Sciences, 2020 - mdpi.com
Featured Application 1. The hybrid machine learning (HML) classifier can easily classify the
subjects (healthy and bruxism), sleep stages (w and REM), and both with high accuracy. 2 …

Recent developments in wearable NEMS/MEMS-based smart infrared sensors for healthcare applications

B Padha, I Yadav, S Dutta, S Arya - ACS Applied Electronic …, 2023 - ACS Publications
Incorporating nano-and microelectromechanical systems (NEMS/MEMS)-based sensors in
clothing and developing more compact and flexible devices have gained popularity recently …