Measurements of Sit-to-Stand Timing and Symmetry From Bed Pressure Sensors

Arcelus, Amaya; Veledar, I.; Goubran, Rafik; Knoefel, Frank; Sveistrup, Heidi; Beznoska, Martin

doi:10.1109/tim.2010.2089171

Cited by 47 publications

(31 citation statements)

References 21 publications

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“…It is important to note, however, that if the timing of the bed transfer is of interest, then another algorithm would need to be used. The time it takes to rise from the sitting position is approximately 5 seconds or less [11]. This period of time is much shorter that the margin of error calculated for the algorithm used in this study.…”

Section: Discussionmentioning

confidence: 78%

“…Past research on pressure sensors has shown that this type of technology can be used to determine bed occupancy, calculate sit-to-stand times and breathing rates [11][12] using short term recordings. However, algorithms used in this previous work would not be feasible to use for long term recordings without segmentation to isolate useable sections of data for the algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Bed occupancy measurements using under mattress pressure sensors for long term monitoring of community-dwelling older adults

Taylor

Grant

Knoefel

et al. 2013

2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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-There is a growing demand for systems that support independent living into advanced age. Technologies that monitor changes in the amount of time older adults spend in bed have the potential to detect critical changes in mobility and support earlier health intervention. Although under mattress sensors have been used previously, processing algorithms were designed for short term monitoring. The objective of this paper was to develop an algorithm and determine optimal sampling rate to obtain bed occupancy characteristics over the longer term. Under mattress sensors were installed in the home of an older adult and data collected over a 3 month period. A processing algorithm was developed to extract bed occupancy information including time in bed, number of bed exits and time of first morning exit. Data were compared using various sampling rates and processing times. Findings indicate that the ideal down sample time for the application was 5 seconds (0.2Hz) and that computational time requirements could be reduced significantly without sacrificing the ability to accurately measure the total time spent in bed and number of bed exits. Features of bed occupancy were plotted and patterns discovered which may be of interest to health clinicians and sleep researchers.

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Section: Discussionmentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Bed occupancy measurements using under mattress pressure sensors for long term monitoring of community-dwelling older adults

Taylor

Grant

Knoefel

et al. 2013

2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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“…This latter finding supports our original hypothesis and offers promise that under mattress pressure sensors can play a role in monitoring changes that occur over time among frail older adults in the home context. The home context presents a number of differences from highly controlled laboratory situations where correlations have been found to be higher 11,12 . This study has identified some of these particularities which are important to recognize for the development of viable home monitoring systems.…”

Section: Discussionmentioning

confidence: 99%

“…One such tool for monitoring this phase of the STS transfer on a continual basis is under-mattress pressure technology. This type of technology is placed under a bed mattress and uses pressure change to calculate STS time [11][12][13] . We have previously shown that under-mattress pressure sensors can differentiate between healthy older adults and those with mobility impairments on the basis of STS time in the laboratory environment 11 .…”

Section: S I T -T O -S T a N D T I M I N Gmentioning

confidence: 99%

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Sit-To-Stand (STS) timing among older adults in their homes: Two measurement approaches

Grant¹,

Bryanton²,

Taylor³

et al. 2014

Gerontechnology

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, Sit-to-stand (STS) timing among older adults in their homes: Two measurement approaches. Gerontechnology 2014;12(3):153-158; doi:10.4017/gt.2014.12.3.006.00 Sit-to-stand (STS) times required by older adults exiting from their beds at home were compared simultaneously using under mattress pressure sensor technology and video analysis. Six older adults consented to participate in the study and had under mattress pressure technology installed in their homes. Participants were visited monthly over a period of 2-10 months by a researcher who asked them to perform three bed exits which were videotaped. The pressure sensor technology calculated a portion of STS time based on changes in pressure between the end of stable sitting on the edge of the bed and pressure leaving the bed. The video analysis approach calculated this corresponding initial phase of the same STS transfer by determining the difference between the first forward movement from the quiet sitting position and the initiation of vertical rise. The remaining period of vertical rise into a complete standing position was calculated using video analysis but not pressure sensor technology. A Spearman's rank order correlation analysis revealed that there was a moderate, positive correlation between the video and pressure-sensor measures of the initial phase of STS which was statistically significant (r s =0.50, n=97, p<0.001). Wilcoxon signed-rank tests indicated that pressure sensor times were longer (Z=-7.91, p<0.000) and more variable than video times (Z=-3.14, p=0.002). Analysis of video data revealed that this initial phase of STS represented between 15 to 81% of the total STS time among the 97 sampled STS in this study. Results highlight how the home environment presents a number of conditions affecting differences in STS values obtained by each of these measurement approaches.

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