A Piezoresistive Array-Based Force Sensing Technique for Sleeping Posture and Respiratory Rate Detection for SAS Patients

Zihao, Wang; Sui, Zhipeng; Zhang, Aojie; Wang, Renrui; Zhang, Zhao; Lin, Feng; Chen, Junliang; Gao, Shuo

doi:10.1109/jsen.2021.3134823

Cited by 6 publications

(6 citation statements)

References 47 publications

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“…We attempted to enhance this factor by reducing the dependency on sleeping positions by improving the sensitivity of the sensors. Compared to the works in [34,35,[57][58][59] which are using similar technology, the performance of the system in terms of accuracy of the cardiorespiratory parameters has been improved. On the other hand, the fiber-optic-based system in [42,67], in general, delivers greater performance disregarding the complexity and cost of the system.…”

Section: Improvements Applications and Opportunitiesmentioning

confidence: 99%

“…Unobtrusiveness: does not interfere with the regular sleeping positions nor impose additional activities. Not considering the wearable devices and camera-based vital signs monitoring during sleep, this work and comparable studies such as those in [34,35,42,[57][58][59]67] are using the similar method of deployment for the sensors, which are under the mattress and on the bed slatter. However, the work resolves the issue, to some extent, of unobtrusive deployment of FSR sensors in bed and pillow cases [68].…”

Section: Improvements Applications and Opportunitiesmentioning

confidence: 99%

“…The authors in [58], used flexible piezoresistive architectures and machine learning algorithms to develop an integrated sleep monitoring system. This low-cost and privacyprotecting system includes a flexible pressure-sensing pad, in the form of a piezoresistive array for capturing the pressure distribution during sleep, and the readout circuit.…”

Section: Introductionmentioning

confidence: 99%

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Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary Study

Haghi

Asadov

Boiko

et al. 2023

Sensors

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Sleep disorders can impact daily life, affecting physical, emotional, and cognitive well-being. Due to the time-consuming, highly obtrusive, and expensive nature of using the standard approaches such as polysomnography, it is of great interest to develop a noninvasive and unobtrusive in-home sleep monitoring system that can reliably and accurately measure cardiorespiratory parameters while causing minimal discomfort to the user’s sleep. We developed a low-cost Out of Center Sleep Testing (OCST) system with low complexity to measure cardiorespiratory parameters. We tested and validated two force-sensitive resistor strip sensors under the bed mattress covering the thoracic and abdominal regions. Twenty subjects were recruited, including 12 males and 8 females. The ballistocardiogram signal was processed using the 4th smooth level of the discrete wavelet transform and the 2nd order of the Butterworth bandpass filter to measure the heart rate and respiration rate, respectively. We reached a total error (concerning the reference sensors) of 3.24 beats per minute and 2.32 rates for heart rate and respiration rate, respectively. For males and females, heart rate errors were 3.47 and 2.68, and respiration rate errors were 2.32 and 2.33, respectively. We developed and verified the reliability and applicability of the system. It showed a minor dependency on sleeping positions, one of the major cumbersome sleep measurements. We identified the sensor under the thoracic region as the optimal configuration for cardiorespiratory measurement. Although testing the system with healthy subjects and regular patterns of cardiorespiratory parameters showed promising results, further investigation is required with the bandwidth frequency and validation of the system with larger groups of subjects, including patients.

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Section: Improvements Applications and Opportunitiesmentioning

confidence: 99%

Section: Improvements Applications and Opportunitiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary Study

Haghi

Asadov

Boiko

et al. 2023

Sensors

View full text Add to dashboard Cite

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“…Human behaviors on bed can also be monitored using sensors mounted to a mat or bedsheet, bed, and pillow [19]- [24]. For example, to detect human postures, a thick pressure-sensitive bedsheet was utilized, as in [20].…”

Section: Introductionmentioning

confidence: 99%

“…The work in [24] used piezoelectric and pressure sensors put under the mattress, while the authors in [23] described a smart mat system for sleep position monitoring based on a dense flexible sensor array and printed electrodes. Although the works in [19]- [24] offered useful systems, expert installation, cost, sufficient surroundings, and effective processing solutions are also required.…”

Section: Introductionmentioning

confidence: 99%

A system for monitoring human postures, seizures, and falls from bed using radio and surface electromyography signals

Intongkum,

Sengchuai,

Booranawong

2024

Bulletin EEI

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In this work, a system for monitoring human postures, seizures, and falls from bed using received signal strength indicator (RSSI) and surface electromyography (sEMG) signals is studied through experiments. In this proposed system, a person who is located inside a wireless link is monitored by considering the change in measured RSSI signals as the 2.4 GHz IEEE 802.15.4 signals received at a receiver. Human motions in bed that affect RSSI levels can be captured. Thus, with this technique, it does not raise a privacy concern compared with vision-based technology. Additionally, sEMG signals associated with muscle movements from human postures are recorded from the human body’s abdominal muscles. Eight different activities, including normal and critical events, are tested and evaluated. Experimental results indicate that the proposed system could automatically monitor different human postures in real-time. RSSI and sEMG signals correlated to each posture have their own patterns. Furthermore, the relationship between human behaviors and RSSI and sEMG levels is summarized.

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Automatic Contact-Less Monitoring of Breathing Rate and Heart Rate Utilizing the Fusion of mmWave Radar and Camera Steering System

et al. 2022

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A Piezoresistive Array-Based Force Sensing Technique for Sleeping Posture and Respiratory Rate Detection for SAS Patients

Cited by 6 publications

References 47 publications

Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary Study

Validating Force Sensitive Resistor Strip Sensors for Cardiorespiratory Measurement during Sleep: A Preliminary Study

A system for monitoring human postures, seizures, and falls from bed using radio and surface electromyography signals

Automatic Contact-Less Monitoring of Breathing Rate and Heart Rate Utilizing the Fusion of mmWave Radar and Camera Steering System

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