Multimodal activity monitoring for home rehabilitation of geriatric fracture patients – feasibility and acceptance of sensor systems in the GAL-NATARS study

Marschollek, Michael; Becker, Marcus; Bauer, Jürgen; Bente, Petra; Dasenbrock, Lena; Elbers, Katharina; Hein, Andreas; Kolb, Gerald; Künemund, Harald; Lammel-Polchau, Christopher; Meis, Markus; Schwabedissen, H. Meyer zu; Remmers, Hartmut; Schulze, Mareike; Steen, Enno-Edzard; Thoben, Wilfried; Wang, Ju; Wolf, Klaus-Hendrik; Haux, Reinhold

doi:10.3109/17538157.2014.931852

Cited by 33 publications

(24 citation statements)

References 12 publications

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“…The result is one feature per day. The mathematical formulation is (1) Where n is the number of sensors installed in the flat, j the 8 seconds time window of the day and 1 the indicator function defined on the set A of all sensor events. In other words, the indicator function is 1 if there is a sensor event e from sensor i in time window j and 0 if there is no event.…”

Section: Preprocessingmentioning

confidence: 99%

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2021

IJU

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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-Physical-Performance-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.

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Section: Preprocessingmentioning

confidence: 99%

“…Smart home sensors are respecting the privacy of the inhabitant and are well accepted among the target group. They get acquainted to the sensors in a few days and do not notice the sensors anymore [1]. The mobility of elderly people is one key indicator for their physical and mental condition.…”

Section: Introductionmentioning

confidence: 99%

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2021

IJU

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“…In the context of new ways for health care, the Whole System Demonstrator project was discussed as a key project of significant importance to the authors (WSD, e.g. [110]) as well as the GAL-NATARS study ( [111], see also [112]).…”

Section: Some Key Projects and Visionsmentioning

confidence: 99%

Health-Enabling and Ambient Assistive Technologies: Past, Present, Future

Haux

Koch²,

Lovell³

et al. 2016

Yearb Med Inform

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SummaryBackground: During the last decades, health-enabling and ambient assistive technologies became of considerable relevance for new informatics-based forms of diagnosis, prevention, and therapy. Objectives: To describe the state of the art of health-enabling and ambient assistive technologies in 1992 and today, and its evolution over the last 25 years as well as to project where the field is expected to be in the next 25 years. In the context of this review, we define health-enabling and ambient assistive technologies as ambiently used sensor-based information and communication technologies, aiming at contributing to a person's health and health care as well as to her or his quality of life. Methods: Systematic review of all original articles with research focus in all volumes of the IMIA Yearbook of Medical Informatics. Surveying authors independently on key projects and visions as well as on their lessons learned in the context of health-enabling and ambient assistive technologies and summarizing their answers. Surveying authors independently on their expectations for the future and summarizing their answers. Results: IMIA Yearbook papers containing statements on health-enabling and ambient assistive technologies appear first in 2002. These papers form a minor part of published research articles in medical informatics. However, during recent years the number of articles published has increased significantly. Key projects were identified. There was a clear progress on the use of technologies. However proof of diagnostic relevance and therapeutic efficacy remains still limited. Reforming health care processes and focussing more on patient needs are required. Conclusions: Health-enabling and ambient assistive technologies remain an important field for future health care and for interdisciplinary research. More and more publications assume that a person's home and their interaction therein, are becoming important components in health care provision, assessment, and management.

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“…However, a continuous monitoring of the body weight by professionals exceeds their capacities and self-monitoring tends to be unreliable in the target group of older (pre-) frail adults [6]. Low-cost, unobtrusive ambient sensor systems are well-accepted among the group of older adults if installed in a flat for continuous monitoring [7,8]. The aim of this contribution is to show that the meal preparation time (key performance indicator, KPI) is associated with body weight changes as an indicator for impending malnutrition.…”

Section: Introductionmentioning

confidence: 99%

Detecting Impending Malnutrition of (Pre-) Frail Older Adults in Domestic Smart Home Environments

Friedrich¹,

Bauer

Hein³

et al. 2021

Nutrients

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Malnutrition is a well-known risk factor for deteriorated physical function, disability and loss in independence in older adults. An unintended loss in body weight of more than 5% in 3 months is one indicator for malnutrition. In this study we examined the relationship between meal preparation time, hand grip strength, and body weight in order to map impending nutritional problems using ambient sensors. Data were collected in the domestic environments of 20 (pre-) frail older adults aged 85.75 y (Standard Deviation: 5.19 y) over 10-months of observation. Collecting included physical function and nutritional status of the participants and meal preparation time by a combination of motion and power sensor events. Analysis was done by rank correlation of hand grip strength, body weight, and meal preparation time. Ten participants aged 85.1 years (Standard Deviation: 4.6 y) were included. The results show a significant correlation (≥0.99) of the meal preparation time with the hand grip strength. This result validated the meal preparation time as a suitable measure for analysing the correlation between meal preparation time and body weight, and a significant correlation (≥0.99) found. Hence the meal preparation time could be used as an indicator for malnutrition. However, causalities have to be conducted by further clinical studies.

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Multimodal activity monitoring for home rehabilitation of geriatric fracture patients – feasibility and acceptance of sensor systems in the GAL-NATARS study

Abstract: Home-monitoring technologies were well-accepted by our participants. The information content of the data still needs to be evaluated with regard to clinical outcome parameters as well as the effect on the quality of life before recommending large-scale implementations.

Cited by 33 publications

References 12 publications

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Health-Enabling and Ambient Assistive Technologies: Past, Present, Future

Detecting Impending Malnutrition of (Pre-) Frail Older Adults in Domestic Smart Home Environments

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