Low-power Continuous Heart and Respiration Rates Monitoring on Wearable Devices

Degtyarenko, Illya; Slyusarenko, Kostyantyn; Omelchenko, Andrii; Рябов, В. В.; Chyzhyk, Sviatoslav

doi:10.1109/icassp.2019.8683825

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Auscultation, or the listening to and classification of a body’s internal noises, has traditionally required the use of a stethoscope by a qualified expert. The use of electret microphones and piezoelectric sensors for auscultation as well as various sensing approaches for categorization have, however, been the subject of recent research [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. Measures of lung health can be obtained from respiratory activities.…”

Section: Lung Sound and Ecg Sensor Signal Fusionmentioning

confidence: 99%

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis

Moon,

Lee

2023

Sensors

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Wireless sensing systems are required for continuous health monitoring and data collection. It allows for patient data collection in real time rather than through time-consuming and expensive hospital or lab visits. This technology employs wearable sensors, signal processing, and wireless data transfer to remotely monitor patients’ health. The research offers a novel approach to providing primary diagnostics remotely with a digital health system for monitoring pulmonary health status using a multimodal wireless sensor device. The technology uses a compact wearable with new integration of acoustics and biopotentials sensors to monitor cardiovascular and respiratory activity to provide comprehensive and fast health status monitoring. Furthermore, the small wearable sensor size may stick to human skin and record heart and lung activities to monitor respiratory health. This paper proposes a sensor data fusion method of lung sounds and cardiograms for potential real-time respiration pattern diagnostics, including respiratory episodes like low tidal volume and coughing. With a p-value of 0.003 for sound signals and 0.004 for electrocardiogram (ECG), preliminary tests demonstrated that it was possible to detect shallow breathing and coughing at a meaningful level.

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Section: Lung Sound and Ecg Sensor Signal Fusionmentioning

confidence: 99%

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis

Moon,

Lee

2023

Sensors

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“…Nonetheless, PPG provides only HR and sometimes ResR with the appropriate signal processing. Proposals of wearable sensors to acquires RespR signals include strain sensors [3], temperature sensors [4] and accelerometers [5], to name some. Their power budgets are tailored to be as low as desired but, again, they are only able to deliver a respiratory signal.…”

Section: Introductionmentioning

confidence: 99%

Simple low-power demodulator for the measurement of basal and physiological changes of electrical bioimpedance

Serrano-Finetti

Hornero

Casas

2022

2022 IEEE International Workshop on Metrology for Industry 4.0 &Amp; IoT (MetroInd4.0&IoT)

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Wearable sensors constitute a growing trend both as a research tool as well as an end-consumer products. In the physiological signal monitoring fields, the changing signals have a low bandwidth hence most sensing techniques are not powerhungry. Electrical bioimpedance is a non-obtrusive sensing technique and is an interesting choice as it can recover both breathing and pulse rate signals. However, it works at comparatively higher frequencies and usually need demodulation circuitry, meaning higher power consumption. In this work, we show an alternative technique to demodulate the impedance response that need very few components and whose power consumption can be tailored as needed. We show that, by using a 24-bit ADC, the respiration and pulse rate signals as well as the basal impedance are recovered from the demodulated signal and further digital band-pass filters that are easily implemented with currently available low-power microcontroller technology. Further, it constitutes a compact solution, as the sensor needs not to change location to measure these signals.

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“…However, we need to overcome some technical challenges to develop genuinely wearable sensors that can become practical and clinically meaningful. Particularly, continuous respiratory monitoring requires to address the technical issues of battery power source, sensor data storage, wireless data communication, and automated diagnosis [ 1 , 2 ]. There have been significant innovations to achieve wearability using a range of material properties, structure, and integration.…”

Section: Introductionmentioning

confidence: 99%

Extraction and Analysis of Respiratory Motion Using a Comprehensive Wearable Health Monitoring System

George

Moon

Lee

2021

Sensors

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Respiratory activity is an important vital sign of life that can indicate health status. Diseases such as bronchitis, emphysema, pneumonia and coronavirus cause respiratory disorders that affect the respiratory systems. Typically, the diagnosis of these diseases is facilitated by pulmonary auscultation using a stethoscope. We present a new attempt to develop a lightweight, comprehensive wearable sensor system to monitor respiration using a multi-sensor approach. We employed new wearable sensor technology using a novel integration of acoustics and biopotentials to monitor various vital signs on two volunteers. In this study, a new method to monitor lung function, such as respiration rate and tidal volume, is presented using the multi-sensor approach. Using the new sensor, we obtained lung sound, electrocardiogram (ECG), and electromyogram (EMG) measurements at the external intercostal muscles (EIM) and at the diaphragm during breathing cycles with 500 mL, 625 mL, 750 mL, 875 mL, and 1000 mL tidal volume. The tidal volumes were controlled with a spirometer. The duration of each breathing cycle was 8 s and was timed using a metronome. For each of the different tidal volumes, the EMG data was plotted against time and the area under the curve (AUC) was calculated. The AUC calculated from EMG data obtained at the diaphragm and EIM represent the expansion of the diaphragm and EIM respectively. AUC obtained from EMG data collected at the diaphragm had a lower variance between samples per tidal volume compared to those monitored at the EIM. Using cubic spline interpolation, we built a model for computing tidal volume from EMG data at the diaphragm. Our findings show that the new sensor can be used to measure respiration rate and variations thereof and holds potential to estimate tidal lung volume from EMG measurements obtained from the diaphragm.

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Low-power Continuous Heart and Respiration Rates Monitoring on Wearable Devices

Cited by 4 publications

References 12 publications

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis

Simple low-power demodulator for the measurement of basal and physiological changes of electrical bioimpedance

Extraction and Analysis of Respiratory Motion Using a Comprehensive Wearable Health Monitoring System

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