A Pressure Sensitive Home Environment

Jones, Megan; Arcelus, Amaya; Goubran, Rafik; Knoefel, Frank

doi:10.1109/have.2006.283799

Cited by 20 publications

(17 citation statements)

References 8 publications

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“…Pressure sensing has been shown to provide a valuable yet unobtrusive method of data collection regarding a smart home occupant's interactions with their surroundings [7] [8]. Three Kinotex® pressure sensors manufactured by Tactex Controls Inc. were embedded in polyethylene foam and placed on each of the two commode bars as shown in Figure 1.…”

Section: B Commode Bar Instrumentationmentioning

confidence: 99%

Analysis of commode grab bar usage for the monitoring of older adults in the smart home environment

Arcelus

Holtzman

Goubran

et al. 2009

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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The occurrence of falls inside the home is a common yet potentially hazardous issue for adults as they age. Even with the installation of physical aids such as grab bars, weight transfers on and off a toilet or bathtub can become increasingly difficult as a person's level of physical mobility and sense of balance deteriorate. Detecting this deterioration becomes an important goal in fall prevention within a smart home. This paper develops an unobtrusive method of analyzing the usage of toilet grab bars using pressure sensors embedded into the arm rests of a commode. Clinical parameters are successfully extracted automatically from a series of stand-to-sit (StSi) and sit-to-stand (SiSt) transfers performed by a trial group of young and older adults. A preliminary comparison of the parameters indicates differences between the two groups, and aligns well with published characteristics obtained using accelerometers worn on the body. The unobtrusive nature of this method provides a useful tool to be incorporated into a system of continuous monitoring of older adults within the smart home environment.

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Section: B Commode Bar Instrumentationmentioning

confidence: 99%

Analysis of commode grab bar usage for the monitoring of older adults in the smart home environment

Arcelus

Holtzman

Goubran

et al. 2009

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…Yousefi et al (2011) used a commercial pressure mapping system with an eigenspace projection along with a k nearest neighbor (kNN) posture classification algorithm to determine patient's bed posture for pressure sore prevention. Many other studies on bed activity recognition, including body turnover and sleep quality, were laboratory-only experiments (Loos, Ullrich, and Kobayashi 2003;Yonezawa et al 2005;Jones et al 2006).…”

Section: Introductionmentioning

confidence: 97%

Monitoring non-ambulatory posture and activity using moment statistics and Bayesian classifier

Hung

Chiu

Chen

et al. 2013

Journal of the Chinese Institute of Engineers

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Providing an appropriate care plan for the elderly to participate in everyday life activities is important, as is developing the technological means to support physical assessments. Current clinical protocol is generally periodic and subjective stemming from expert assessments and interviews. This paper aims to present a probabilistic framework to efficiently model the posture and activity of non-ambulatory elderly patients, provide evidence for quantitative measurements and assist in the health related quality of life (HRQL) assessment. Pressure distribution data gathered from a developed sensor pad were projected and parameterized using moment statistics as features for static and dynamic activity modeling. The effect of posture angle was reduced by estimation of linear regression and a rotation matrix is used to realign the orientation of posture. A Bayesian classifier with Gaussian mixture model was adopted for posture recognition. A robust decision method based on minimum classification error was applied for the parameter estimation. Several objective evaluations and field trials were performed to investigate the detection performance of posture and activity. Our proposed approach outperformed vector quantization and shows encouraging potential for the development of HRQL indicators.

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“…The research motivation is driven by the possibility of having smart homes provide future benefits to seniors as well as nurses and caregivers. Technologies such as wireless bed sensors have been used to monitor occupants while they are sleeping [1] and embedding technologies such as optical fiber pressure sensors into furniture could be used to monitor occupants throughout the home [2]. This technology has successfully been used to measure the force [3] and estimate the location of the applied force [4] on a set of grab bars placed in the bathroom.…”

Section: Introductionmentioning

confidence: 99%

Sit-to-stand timing measurements using pressure sensitive technology

Veledar

Arcelus

Goubran

et al. 2010

2010 IEEE Instrumentation &Amp; Measurement Technology Conference Proceedings

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Measuring and analyzing the sit-to-stand movement performed by an individual when rising from their bed can be used to document health and mobility. This paper investigates measuring sit-to-stand timing from young healthy subjects using non-invasive pressure sensitive array technology. First, it describes the pressure sensitive array, the experiment setup and data collection process. Next, three methods for measuring sit-tostand timing are examined. These include a method based on the combination of bed and foot pressure, an image-based method and a pressure signal-based method. Challenges, limitations and results are shown for each using data collected from 10 young healthy subjects. The pressure signal-based method measures the sit-to-stand time more effectively when comparing to video data. The further development of this method is then presented; this includes analyzing the pressure signal to detect phases that make up the sit-to-stand movement and a sample result for one young healthy subject is presented.

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A Pressure Sensitive Home Environment

Cited by 20 publications

References 8 publications

Analysis of commode grab bar usage for the monitoring of older adults in the smart home environment

Analysis of commode grab bar usage for the monitoring of older adults in the smart home environment

Monitoring non-ambulatory posture and activity using moment statistics and Bayesian classifier

Sit-to-stand timing measurements using pressure sensitive technology

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