scholarly journals Assessing the Mobility of Elderly People in Domestic Smart Home Environments

2020 ◽  
Author(s):  
Björn Friedrich ◽  
Enno-Edzard Steen ◽  
Sebastian Fudickar ◽  
Andreas Hein
Keyword(s):  
Elderly People ◽  
Smart Home ◽  
Continuous Monitoring ◽  
Early Stage ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Physical Strength ◽  
Assessment Scores ◽  
Mobility Assessment ◽  
Smart Home Environments

A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the wellestablished mobility assessment Short-Physical-Performance-Battery and Tinetti. We use the average number of motion sensor events for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.

scholarly journals Analysing the Correlation of Geriatric Assessment Scores and Activity in Smart Homes

2021 ◽  
Vol 12 (2) ◽  
pp. 1-15
Author(s):  
Björn Friedrich ◽  
Enno-Edzard Steen ◽  
Sebastian Fudickar ◽  
Andreas Hein
Keyword(s):  
Elderly People ◽  
Real World ◽  
Strong Correlation ◽  
Continuous Monitoring ◽  
Early Stage ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Physical Strength ◽  
Assessment Scores ◽  
Activity Measure

A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the well-established mobility assessments Short-PhysicalPerformance-Battery, Tinetti and Timed Up & Go. We use the average number of motion sensor events as activity measure for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.

IoT based Context-Aware Smart Home Caregivers System for Monitoring Elderly People

2020 ◽  
pp. 1-6
Author(s):  
Laura Schaefer ◽  
Matt Bowden
Keyword(s):  
Health Status ◽  
Real Time ◽  
Elderly People ◽  
Smart Home ◽  
Early Stage ◽  
The Elderly ◽  
Daily Activities ◽  
Context Aware ◽  
Healthcare Applications ◽  
The People

In pervasive computing, the area of contextawareness is considered as an important technology and also plays a important role in the area of healthcare environments. In this paper we propose a system for elderly people signs monitoring and critical health conditions which is sends to the caregivers to identify the daily activities by using internet of things (IoT) this can be done in real-time. For example the elderly people who are not well in daily activities like current health status is “normal” or “critical” and the caregivers can give the early suggestions to the people who are in nearby. We have build a fuzzy logic from the beginning of data acquisition, processing of the data namely filtering , aggregating it into contextual information and reasoning to identify the elderly people health condition. Variety of connected devices can modify the remote characteristic, real-time monitoring, measuring and transmitting numerous body health parameters for making the decision and medication. The goal of this paper is to introduce the approach Context Aware Smart Home Caregivers System (CASHCS) to identify the normal and abnormal conditions of the people health status so that doctor can cure the problems in early stage without any complication. So this can be used to build a framework for context-aware healthcare applications.

IoT based Context-Aware Smart Home Caregivers System for Monitoring Elderly People

2020 ◽  
pp. 1-6
Author(s):  
Laura Schaefer ◽  
Matt Bowden
Keyword(s):  
Health Status ◽  
Real Time ◽  
Elderly People ◽  
Smart Home ◽  
Early Stage ◽  
The Elderly ◽  
Daily Activities ◽  
Context Aware ◽  
Healthcare Applications ◽  
The People

In pervasive computing, the area of contextawareness is considered as an important technology and also plays a important role in the area of healthcare environments. In this paper we propose a system for elderly people signs monitoring and critical health conditions which is sends to the caregivers to identify the daily activities by using internet of things (IoT) this can be done in real-time. For example the elderly people who are not well in daily activities like current health status is “normal” or “critical” and the caregivers can give the early suggestions to the people who are in nearby. We have build a fuzzy logic from the beginning of data acquisition, processing of the data namely filtering , aggregating it into contextual information and reasoning to identify the elderly people health condition. Variety of connected devices can modify the remote characteristic, real-time monitoring, measuring and transmitting numerous body health parameters for making the decision and medication. The goal of this paper is to introduce the approach Context Aware Smart Home Caregivers System (CASHCS) to identify the normal and abnormal conditions of the people health status so that doctor can cure the problems in early stage without any complication. So this can be used to build a framework for context-aware healthcare applications.

Intuitive Control on Electric Devices by Smartphones for Smart Home Environments

2016 ◽  
Vol 16 (11) ◽  
pp. 4281-4294 ◽  
Author(s):  
Meng-Shiuan Pan ◽  
Chun-Jie Chen
Keyword(s):  
Smart Home ◽  
Home Environments ◽  
Smart Home Environments

scholarly journals Quantifying Habitual Physical Activity and Sedentariness in Older Adults—Different Outcomes of Two Simultaneously Body-Worn Motion Sensor Approaches and a Self-Estimation

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1877
Author(s):  
Rieke Trumpf ◽  
Wiebren Zijlstra ◽  
Peter Haussermann ◽  
Tim Fleiner
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Community Dwelling ◽  
Habitual Physical Activity ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Healthy Older Adults ◽  
Lower Back ◽  
Hybrid Motion ◽  
Accurate Quantification

Applicable and accurate assessment methods are required for a clinically relevant quantification of habitual physical activity (PA) levels and sedentariness in older adults. The aim of this study is to compare habitual PA and sedentariness, as assessed with (1) a wrist-worn actigraph, (2) a hybrid motion sensor attached to the lower back, and (3) a self-estimation based on a questionnaire. Over the course of one week, PA of 58 community-dwelling subjectively healthy older adults was recorded. The results indicate that actigraphy overestimates the PA levels in older adults, whereas sedentariness is underestimated when compared to the hybrid motion sensor approach. Significantly longer durations (hh:mm/day) for all PA intensities were assessed with the actigraph (light: 04:19; moderate to vigorous: 05:08) when compared to the durations (hh:mm/day) that were assessed with the hybrid motion sensor (light: 01:24; moderate to vigorous: 02:21) and the self-estimated durations (hh:mm/day) (light: 02:33; moderate to vigorous: 03:04). Actigraphy-assessed durations of sedentariness (14:32 hh:mm/day) were significantly shorter when compared to the durations assessed with the hybrid motion sensor (20:15 hh:mm/day). Self-estimated duration of light intensity was significantly shorter when compared to the results of the hybrid motion sensor. The results of the present study highlight the importance of an accurate quantification of habitual PA levels and sedentariness in older adults. The use of hybrid motion sensors can offer important insights into the PA levels and PA types (e.g., sitting, lying) and it can increase the knowledge about mobility-related PA and patterns of sedentariness, while actigraphy appears to be not recommendable for this purpose.

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