Sensor pillow system: Monitoring cardio-respiratory and posture movements during sleep

Lokavee, Shongpun; Watthanawisuth, N.; Mensing, Johannes Ph.; Kerdcharoen, Teerakiat

doi:10.1109/bmeicon.2012.6172021

Cited by 14 publications

(7 citation statements)

References 12 publications

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“…Various types of sensors exist that can be classified in respect to their positioning towards the human body: sensors can be implanted into the body [ 1 , 2 , 3 , 4 , 5 ] and used in various body parts such as in hips [ 6 ], they can be externally attached to bodies or be in the vicinity of bodies (wearable sensors) [ 7 , 8 , 9 , 10 , 11 , 12 , 13 ] and they can be positioned in the environment such as walls and floors of a home [ 14 , 15 , 16 , 17 , 18 ]. Sensors are used for various purposes in regards to disabled people, including but not limited to health monitoring [ 19 ], evacuation and rescue information [ 19 ], indoor navigation aid [ 20 ], smart home systems that aid disabled people to carry out daily activities in the safety and comfort of their homes [ 21 ], real time tracking of disabled people [ 22 ], sensor pillow systems [ 23 ], assistive living [ 24 ], home medical assistance [ 25 ], rehabilitation [ 8 ], physiological monitoring [ 11 ], as health managing system [ 26 ] and for mobile health [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Sensors: Views of Staff of a Disability Service Organization

Wolbring

Leopatra

2013

JPM

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Sensors have become ubiquitous in their reach and scope of application. They are a technological cornerstone for various modes of health surveillance and participatory medicine—such as quantifying oneself; they are also employed to track people with certain as impairments perceived ability differences. This paper presents quantitative and qualitative data of an exploratory, non-generalizable study into the perceptions, attitudes and concerns of staff of a disability service organization, that mostly serve people with intellectual disabilities, towards the use of various types of sensor technologies that might be used by and with their clients. In addition, perspectives of various types of privacy issues linked to sensors, as well data regarding the concept of quantified self were obtained. Our results highlight the need to involve disabled people and their support networks in sensor and quantified-self discourses, in order to prevent undue disadvantages.

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Section: Introductionmentioning

confidence: 99%

Sensors: Views of Staff of a Disability Service Organization

Wolbring

Leopatra

2013

JPM

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“…The options were analyzed against the ideal sensor criteria: (1) flat sensor shape, (2) ability to detect a large pressure range, (3) lower cost. Force-sensing resistors (FSR) are simple tactile sensors [51,68] that are used in applications where changes and differences in pressure need to be detected. These are constructed using conductive polymers, elastomers or semiconducting polymers, piezo-resistive material, conductive wires, fiber-optical, or fiber-grating material.…”

Section: Sensor Designmentioning

confidence: 99%

“…The bedsheet deployed pressure sensors captured pressure mapping images and different postures could be recognized using classifiers. Alternatively, distributed pressure sensors entrenched in the mattress could record any changes in body posture [50][51][52][53]. The pressure-sensitive mats manufactured by S4 sensors recorded the patient's movement between different postures [54].…”

Section: Introductionmentioning

confidence: 99%

CNN-Based Smart Sleep Posture Recognition System

Tang

Kumar

Nadeem

et al. 2021

IoT

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Sleep pattern and posture recognition have become of great interest for a diverse range of clinical applications. Autonomous and constant monitoring of sleep postures provides useful information for reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, and pressure sensors, which are not only expensive but also intrusive in nature, and uncomfortable to use. We propose an unobtrusive and affordable smart system based on an electronic mat called Sleep Mat-e for monitoring the sleep activity and sleep posture of individuals living in residential care facilities. The system uses a pressure sensing mat constructed using piezo-resistive material to be placed on a mattress. The sensors detect the distribution of the body pressure on the mat during sleep and we use convolution neural network (CNN) to analyze collected data and recognize different sleeping postures. The system is capable of recognizing the four major postures—face-up, face-down, right lateral, and left lateral. A real-time feedback mechanism is also provided through an accompanying smartphone application for keeping a diary of the posture and send alert to the user in case there is a danger of falling from bed. It also produces synopses of postures and activities over a given duration of time. Finally, we conducted experiments to evaluate the accuracy of the prototype, and the proposed system achieved a classification accuracy of around 90%.

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“…al. [12] proposed a sleep monitoring and gesture recognition system for patient based on polysomnography. This sensor pillow system employs a 3x3 sensor array of FSR (force sensing resistor) based on polymer thick film device for classifying and recognizing sleep posture.…”

Section: Related Workmentioning

confidence: 99%

Determination of Lying Posture through Recognition of Multitier Body Parts

Kim

Kwon

Hyun-Min

et al. 2019

Wireless Communications and Mobile Computing

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In this paper, we propose a lying posture discrimination algorithm to monitor the behavior pattern of a person lying in bed. Using FSR (force sensing resistor) sensors arranged in a grid structure, three major body parts such as head, shoulder, and hips are identified, and six lying positions are determined based on these body parts. Head, shoulder, and hips are relatively high in pressure and are easy to distinguish due to low movement. In addition, we have effectively limited the search space to identify the above body parts based on standard body dimensions. Experimental results show that there is a correlation between pressure distribution and lying posture. The results of this study can be applied to the monitoring of sleep posture and can also be used as an aid to prevent fall accidents and the occurrence of pressure ulcers of elderly patients who are unable to move.

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Sensor pillow system: Monitoring cardio-respiratory and posture movements during sleep

Cited by 14 publications

References 12 publications

Sensors: Views of Staff of a Disability Service Organization

Sensors: Views of Staff of a Disability Service Organization

CNN-Based Smart Sleep Posture Recognition System

Determination of Lying Posture through Recognition of Multitier Body Parts

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