Detection of bed-exit events using a new wireless bed monitoring assistance

Bruyneel, Marie; Libert, Walter W.; Ninane, Vincent

doi:10.1016/j.ijmedinf.2010.10.007

Cited by 32 publications

(30 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Discussionmentioning

confidence: 99%

“…Most of these studies [8], [12], [40], [41] have been evaluated with healthy adult participants as opposed to older people. Hilbe et al [40] and Bruyneel et al [41] used pressure sensors attached to hospital beds. Najafi et al [8] and Godfrey et al [12] used wearable sensors strapped to participants for activity recognition and evaluated their approaches on data collected from older people, as in our study.…”

Section: Discussionmentioning

confidence: 99%

“…• Our proposed framework for bed-egress recognition is highly responsive and reduces time delays to alarm so that caregivers are given a better opportunity to intervene while patients are undertaking unsupervised risky activities. In contrast, previous methods needed pre-processing of sensor data (such as filtering) [16] or a waiting time for sensors to reach a steady state (≈ 2 min in [41]) prior to generating an alarm. Furthermore, approaches to handling activity label prediction inaccuracies in [8] and [42] rely on initiating notifications (i.e.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People

Wickramasinghe

Ranasinghe

Visvanathan

2017

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

Getting out of bed and ambulating without supervision is identified as one of the major causes of patient falls in hospitals and nursing homes. Therefore, increased supervision is proposed as a key strategy toward falls prevention. An emerging generation of batteryless, lightweight, and wearable sensors are creating new possibilities for ambulatory monitoring, where the unobtrusive nature of such sensors makes them particularly adapted for monitoring older people. In this study, we investigate the use of a batteryless radio-frequency identification (RFID) tag response to analyze bed-egress movements. We propose a bed-egress movement detection framework that includes a novel sequence learning classifier with a set of features derived from bed-egress motion analysis. We analyzed data from 14 healthy older people (66-86 years old) who wore a wearable embodiment of a batteryless accelerometer integrated RFID sensor platform loosely attached over their clothes at sternum level, and undertook a series of activities including bed-egress in two clinical room settings. The promising results indicate the efficacy of our batteryless bed-egress monitoring framework.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People

Wickramasinghe

Ranasinghe

Visvanathan

2017

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

show abstract

“…These pressure-sensing measurements can also be used for other health care purposes such as the prevention of pressure ulcers [10,11] as well as monitoring of stumbling when exiting the bed and sleeping disorders [12,13]. Alternatively, several studies have used energy-transmitting devices to obtain data by observing static-charge variations [8,14]. …”

Section: Introductionmentioning

confidence: 99%

An Enhanced Sensing Application Based on a Flexible Projected Capacitive-Sensing Mattress

Chang

Chen

Chang

et al. 2014

Sensors

View full text Add to dashboard Cite

This paper presents a cost-effective sensor system for mattresses that can classify the sleeping posture of an individual and prevent pressure ulcers. This system applies projected capacitive sensing to the field of health care. The charge time (CT) method was used to sensitively and accurately measure the capacitance of the projected electrodes. The required characteristics of the projected capacitor were identified to develop large-area applications for sensory mattresses. The area of the electrodes, the use of shielding, and the increased length of the transmission line were calibrated to more accurately measure the capacitance of the electrodes in large-size applications. To offer the users comfort in the prone position, a flexible substrate was selected and covered with 16 × 20 electrodes. Compared with the static charge sensitive bed (SCSB), our proposed system-flexible projected capacitive-sensing mattress (FPCSM) comes with more electrodes to increase the resolution of posture identification. As for the body pressure system (BPS), the FPCSM has advantages such as lower cost, higher aging-resistance capability, and the ability to sense the capacitance of the covered regions without physical contact. The proposed guard ring design effectively absorbs the noise and interrupts leakage paths. The projected capacitive electrode is suitable for proximity-sensing applications and succeeds at quickly recognizing the sleeping pattern of the user.

show abstract

“…Many care systems have been developed based on activities detected in bed, for example, detection of bed-exit and fall events [Yonezawa et al 2005, Ogawa et al 2008, Bruyneel et al 2011], recognition of sleep pattern and quality [Watanabe et al 2005, Choi et al 2007, Cheng et al 2008, Migliorini et al 2010, and the monitoring of obstructive sleep apnea syndrome (OSAS) [Watanabe et al 2010, Bruyneel et al2013]. In such systems, motion sensing in bed, or bed actigraphy, is often the core technique.…”

Section: Introductionmentioning

confidence: 99%

Development of a Bed-Centered Telehealth System Based on a Motion-Sensing Mattress

Liu

Hsu

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

View full text Add to dashboard Cite

Given the rapid increase in the aging population and the decline in birth rate, there is a growing demand for healthcare services. For the elderly who are living at home or in nursing homes, the bed is an integral part of their daily lives. The monitoring of physical activities in bed can provide valuable information of the status of an elderly person. This paper presents a Bed-Centered Telehealth System (BCTS), which uses the bed as the center of health data collection of telehealth systems implemented in homes and nursing homes. The core sensor of the BCTS is a soft motion-sensing mattress, WhizPAD. WhizPAD collects signals of physical activities in bed, which can be classified into events such as on/off bed, sleep posture, pressure distribution, movement counts, and respiration rate. The BCTS facilitates bed-related real-time monitoring, service reminders for caregivers, and a history of the user's data. Integrated with information and communication systems, caregivers can maintain awareness of elderly persons' daily activities and needs by using their mobile devices to access the WhizPAD and further provide the necessary care for them.

show abstract

Detection of bed-exit events using a new wireless bed monitoring assistance

Cited by 32 publications

References 15 publications

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People

Sequence Learning with Passive RFID Sensors for Real-Time Bed-Egress Recognition in Older People

An Enhanced Sensing Application Based on a Flexible Projected Capacitive-Sensing Mattress

Development of a Bed-Centered Telehealth System Based on a Motion-Sensing Mattress

Contact Info

Product

Resources

About