Measuring nightly activity, body weight and body weight change rate with a sensor equipped bed

Schrempf, Andreas; Schossleitner, Gerold; Blaha, Armin; Leipold, Stefan

doi:10.1109/iembs.2010.5626643

Cited by 4 publications

(1 citation statement)

References 10 publications

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“…So far, various body weight monitoring systems have developed. Some of them work using fiber optic loops [2], pressure sensor [3], weight sensor [4] and force sensor [5], the other chose to use structured light sensor [6]. Some researcher investigates particular parameter, body mass index using speech signal [7] [8].…”

Section: Introductionmentioning

confidence: 99%

Weight monitoring system for newborn incubator application

Widianto¹,

Nurfitri²,

Mahatidana³

et al. 2018

AIP Conference Proceedings

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Abstract. We proposed weight monitoring system using load cell sensor for newborn incubator application. The weight sensing system consists of a load cell, conditioning signal circuit, and microcontroller Arduino Uno R3. The performance of the sensor was investigated by using the various weight from 0 up to 3000 g. Experiment results showed that this system has a small error of 4.313% and 12.5 g of threshold and resolution value. Compared to the typical baby scale available in local market, the proposed system has a lower error value and hysteresis.

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Section: Introductionmentioning

confidence: 99%

Weight monitoring system for newborn incubator application

Widianto¹,

Nurfitri²,

Mahatidana³

et al. 2018

AIP Conference Proceedings

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A Proposal of New Multifunctional Pressure Sensor Based on PVDF Films

Kimoto

Shimada

2013

IEEE Trans. Instrum. Meas.

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A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study

et al. 2018

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BackgroundThe prevalence of self-reported shoulder pain in the UK has been estimated at 16%. This has been linked with significant sleep disturbance. It is possible that this relationship is bidirectional, with both symptoms capable of causing the other. Within the field of sleep monitoring, there is a requirement for a mobile and unobtrusive device capable of monitoring sleep posture and quality. This study investigates the feasibility of a wearable sleep system (WSS) in accurately detecting sleeping posture and physical activity.MethodsSixteen healthy subjects were recruited and fitted with three wearable inertial sensors on the trunk and forearms. Ten participants were entered into a ‘Posture’ protocol; assuming a series of common sleeping postures in a simulated bedroom. Five participants completed an ‘Activity’ protocol, in which a triphasic simulated sleep was performed including awake, sleep and REM phases. A combined sleep posture and activity protocol was then conducted as a ‘Proof of Concept’ model. Data were used to train a posture detection algorithm, and added to activity to predict sleep phase. Classification accuracy of the WSS was measured during the simulations.ResultsThe WSS was found to have an overall accuracy of 99.5% in detection of four major postures, and 92.5% in the detection of eight minor postures. Prediction of sleep phase using activity measurements was accurate in 97.3% of the simulations. The ability of the system to accurately detect both posture and activity enabled the design of a conceptual layout for a user-friendly tablet application.ConclusionsThe study presents a pervasive wearable sensor platform, which can accurately detect both sleeping posture and activity in non-specialised environments. The extent and accuracy of sleep metrics available advances the current state-of-the-art technology. This has potential diagnostic implications in musculoskeletal pathology and with the addition of alerts may provide therapeutic value in a range of areas including the prevention of pressure sores.Electronic supplementary materialThe online version of this article (10.1186/s40001-018-0326-9) contains supplementary material, which is available to authorized users.

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Measuring nightly activity, body weight and body weight change rate with a sensor equipped bed

Cited by 4 publications

References 10 publications

Weight monitoring system for newborn incubator application

Weight monitoring system for newborn incubator application

A Proposal of New Multifunctional Pressure Sensor Based on PVDF Films

A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study

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