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

Abstract

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.

Context-aware smart home monitoring through the analysis of pressure sequences

“…To aid in these transfers, the Canadian Standards Association recommends the use of grab bars affixed to the wall or in the form of toilet commodes [91]. 4 Significant portions of the contents in this section have also been published in either [19] or [21]. 89…”

“…Sources of context were introduced to the monitoring system in Chapter 7 including an algorithm for the extraction of clinical features from pressure-sensitive grab bars. The algorithm components were published in [19] and [20], the results of the clinical trials were published in [21] and related implications for the clinical field were published in [22]. A simulated context-aware environment was presented in Chapter 8 to demonstrate the function of the smart home monitoring system and has also been published in [23].…”

Robust Ambient Multisensor Signal Fusion Towards Clinical Data Analytics

“…4.3) was part of a larger work examining estimating contact force and location along grab bars. The work was included in three publications [47,48,50].…”

“…Effect of sensor response on the shape of a simulated breath signal according to four values of mean loading:[50,100,140,180] N.…”

Feature extraction for the differentiation of dry and wet cough sounds

“…Furthermore, it will help the elderly people to live and stay independent. Elderly patients can decide where and how they want to live and at the same time take advantage of high quality healthcare services.In Canada and all other countries, the aging population is growing as compared to other age groups[6] [43]. This trend would make it challenging for hospitals and healthcare facilities to provide various medical services to the aging population[44] [45].Another factor that makes this issue more challenging is patients who suffer from chronic diseases, such as heart disease, stroke, cancer, chronic respiratory diseases and diabetes.Chronic diseases are long lasting and slow progressing diseases which need constant care and supervision [46][47] [48].…”