A novel adhesive biosensor system for detecting respiration, cardiac, and limb movement signals during sleep: validation with polysomnography

Abstract

BackgroundAlthough in-lab polysomnography (PSG) remains the gold standard for objective sleep monitoring, the use of at-home sensor systems has gained popularity in recent years. Two categories of monitoring, autonomic and limb movement physiology, are increasingly recognized as critical for sleep disorder phenotyping, yet at-home options remain limited outside of research protocols. The purpose of this study was to validate the BiostampRC® sensor system for respiration, electrocardiography (ECG), and leg electromyography (EMG) against gold standard PSG recordings.MethodsWe report analysis of cardiac and respiratory data from 15 patients and anterior tibialis (AT) data from 19 patients undergoing clinical PSG for any indication who simultaneously wore BiostampRC® sensors on the chest and the bilateral AT muscles. BiostampRC® is a flexible, adhesive, wireless sensor capable of capturing accelerometry, ECG, and EMG. We compared BiostampRC® data and feature extractions with those obtained from PSG.ResultsThe heart rate extracted from BiostampRC® ECG showed strong agreement with the PSG (cohort root mean square error of 5 beats per minute). We found the thoracic BiostampRC® respiratory waveform, derived from its accelerometer, accurately calculated the respiratory rate (mean average error of 0.26 and root mean square error of 1.84 breaths per minute). The AT EMG signal supported periodic limb movement detection, with area under the curve of the receiver operating characteristic curve equaling 0.88. Upon completion, 88% of subjects indicated willingness to wear BiostampRC® at home on an exit survey.ConclusionThe results demonstrate that BiostampRC® is a tolerable and accurate method for capturing respiration, ECG, and AT EMG time series signals during overnight sleep when compared with simultaneous PSG recordings. The signal quality sufficiently supports analytics of clinical relevance. Larger longitudinal in-home studies are required to support the role of BiostampRC® in clinical management of sleep disorders involving the autonomic nervous system and limb movements.

Breathing Monitoring and Pattern Recognition with Wearable Sensors

“…Accelerometers can be used to capture the respiratory movements during inhalation and exhalation events [29]. An adhesive sensor (called BiostampRC®) made of a triaxial accelerometer that can be placed on the chest wall (Figure 6b) has been used [29].…”

“…Filters can be applied to minimize high-frequency noise, preserving the shape of the respiratory signal [29]. A band-pass filter with cutoff frequencies of 0.1 and 1.5 Hz was applied to compensate for possible drifts and to reduce the total noise level in the signals [10].…”

Recent advances in wearable sensors and portable electronics for sleep monitoring

“…LED & photodiode Wrist (Braun et al, 2020) Forehead (Beppler et al, 2018) Ear (Davies et al, 2020) IPG Dry electrode Wrist (Schneider et al, 2018) Pulse pressure Pressure sensor Wrist (Meng et al, 2020) Respiration Body movement Strain gauge, accelerometer, magnetometer Chest (Klum et al, 2020), (Ding et al, 2018), (Ramírez et al, 2019), (Di Rienzo et al, 2018), (Milici et al, 2018) Head (Arnal et al, 2019) Air flow Humidity sensor Nose (Jin et al, 2017) Lung sound Stethoscope Chest (Klum et al, 2020) Movement EMG Dry electrode Leg (Jortberg et al, 2018) Actigraphy Accelerometer, gyroscope, magnetometer Wrist (Liao et al, 2020), (Kwasnicki et al, 2018) Leg (Bobovych et al, 2020) Chest (Ilen et al, 2019), (Kwasnicki et al, 2018) Body position Accelerometer, gyroscope, magnetometer Wrist (Kwasnicki et al, 2018) Chest (Yun et al, 2020), (Kwasnicki et al, 2018) Nose (Manoni et al, 2020) Others EDA Dry electrode Wrist (Romine et al, 2019), (Kim et al, 2021) Finger (Lam and Szypula, 2018) Tongue deformation Ultrasonic transducer Chin (Weng et al, 2017) Body temperature Thermometer Chest, wrist (Di Rienzo et al, 2018), (Liao et al, 2020) Snoring sound Microphone Forehead (Levendowski et al, 2017) ll OPEN…”

“…These measurements from limbs are used to identify when the patients are awake and to detect various sleep disorders, including periodic limb movements in sleep (PLMS), alternating leg muscle activation (ALMA), and hypnagogic foot tremor (HFT). To achieve the monitoring of limb movements at home, BioStampRC from MC10 (Massachusetts, United States) provides a wireless, flexible, adhesive patch-type device that is capable of measuring various electrophysiological signals, including leg EMG ( Figure 6 A) ( Jortberg et al., 2018 ). BioStampRC shows comparable leg EMG signal quality to the PSG leg EMG measurement and can detect events of PLMS ( Figure 6 B).…”

“… (B) Comparison of PLMS event detection between the patch in (A) and the conventional PSG for performance validation. Reproduced with permission, from ref ( Jortberg et al., 2018 ), Copyright 2018, Dovepress. (C) Wrist wearable electronics incorporating accelerometer, ambient light sensor, and finger PPG sensor to monitor the user's activity, HR, and strength of ambient light for sleep-wake pattern identification.…”