Low intrusive Ehealth monitoring: human posture and activity level detection with an intelligent furniture network

Heikkilä, Tapio; Strömmer, Esko; Kivikunnas, Sauli; Järviluoma, Markku; Korkalainen, Marko; Kyllönen, Vesa; Sarjanoja, Esa-Matti; Peltomaa, Irina

doi:10.1109/mwc.2013.6590051

Cited by 8 publications

(10 citation statements)

References 10 publications

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“…2. Environmental: in this approach, the sensors are deployed in the outdoor space environment or on furniture that will be used by the elderly demographic [32].…”

Section: Discussionmentioning

confidence: 99%

“…GPS-based tracking systems can enhance location and mobility awareness, which in turn, assists healthcare providers in detecting adverse health conditions and to quickly act upon them. Heikkilä et al [32] modelled an intelligent furniture network which could be used in an outdoor space for tracking residents' posture and detection of abnormal living patterns using a very low-cost low-intrusive capacitive proximity sensors based on Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 Medium Access Control (MAC) and IEEE 802.15.4a hardware layer. In the proposed architecture, the sensors were integrated into the furniture which include a chair, a sofa and a bed, and then connected to a microcontroller based wireless sensor network (WSN) master node and a gateway as depicted in Figure 4.…”

Section: Localization Of Affected Older Persons With Easy To Use Commmentioning

confidence: 99%

“…However, eHealth communication technologies are also expected to be userfriendly, ubiquitous and user-centric in order to maximize their benefit [7]. In addition, overall persistence for events and occasional temporal persistence for sensor data stream represent two key requirements for architectural development for eHealth monitoring [32].…”

Section: Reference Architecture For Ehealthmentioning

confidence: 99%

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Innovative and Assistive eHealth Technologies for Smart Therapeutic and Rehabilitation Outdoor Spaces for the Elderly Demographic

Marques¹,

McIntosh²,

Valera³

et al. 2020

Preprint

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The use of technology for social connectivity and achieving engagement goals is increasingly essential to the overall well-being of our rapidly ageing population. While much of the extant literature has focused on home automation and indoor remote health monitoring; there is a growing literature that finds personal health and overall well-being improves when physical activities are conducted outdoors. This study presents a review of possible innovative and assistive eHealth technologies suitable for smart therapeutic and rehabilitation outdoor spaces for older persons. The article also presents key performance metrics required of eHealth technologies to ensure robust, timely and reliable biometric data transfer between patients in a therapeutic landscape environment and respective medical centres. A literature review of relevant publications with a primary focus of integrating sensors and eHealth technologies in outdoor spaces to collect and transfer data from the elderly demographic who engage such built landscapes to appropriate stakeholders was conducted. A content analysis was carried out to synthesize outcomes of the literature review. The study finds that research in assistive eHealth technologies and interfaces for outdoor therapeutic spaces is in its nascent stages and has limited generalisability. The level of technology uptake and readiness for smart outdoor spaces is still developing and is currently being outpaced by the growth of elderly fitness zones in public spaces. Further research is needed to explore those eHealth technologies with interactive feedback mechanisms that are suitable for outdoor therapeutic environments.

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“…2. Environmental: in this approach, the sensors are deployed in the outdoor space environment or on furniture that will be used by the elderly demographic [32].…”

Section: Discussionmentioning

confidence: 99%

Section: Localization Of Affected Older Persons With Easy To Use Commmentioning

confidence: 99%

Section: Reference Architecture For Ehealthmentioning

confidence: 99%

See 1 more Smart Citation

Innovative and Assistive eHealth Technologies for Smart Therapeutic and Rehabilitation Outdoor Spaces for the Elderly Demographic

Marques¹,

McIntosh²,

Valera³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In [14], presents a functional tool for gait abnormality detection that uses video analysis through automatic marker tracking. In [15], Heikkil et. al.…”

Section: Related Workmentioning

confidence: 99%

Design & Development of IoT Based Rehabilitation Outdoor Landscape for Gait Phase Recognition

Gaddam

Wilkin

Angelova

et al. 2019

2019 13th International Conference on Sensing Technology (ICST)

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Over a few decades, there is a steady accretion of life expectancy in many countries. Significant advances in modern healthcare technologies, medicines and overall health care awareness gave many to lead a prolonged healthy life. Over the past few years, there has been a huge demand for unobtrusive health monitoring systems from both medical professionals and the general populace to use these technologies for understanding the general health well being in order to improve life longevity. However, most of the available technologies for health monitoring are difficult for the general populace to access and most of the developed health monitoring systems are either deployed in a controlled environment or in healthcare facilities, thus severely limiting the ease of access to many, especially the elderly people. For effective health management of elderly people, evidence-based decision making, continuously monitoring the health status of the elderly demographic is paramount. In order to address these issues, we developed an innovative smart IoT based outdoor health monitoring system. The proposed system collects information about the mobility, posture, and overall gait of the person in an easy to access public outdoor setting such as parks, supermarkets etc. It is quite evident from multiple studies, that analysing the gait can be a useful tool in early detection of the declining health of individuals, as mobility is a key factor in any individual's well being. Also, detecting gait disorders earlier will allow for functional relief to the health care system with the possibility of reducing the number and severity of gait disorders through early intervention.

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“…Oguntala et al proposed the ambient human activity recognition approach using passive radio frequency identification (RFID) tags to unobtrusively sampled target activities [25,26]. Heikkel et al proposed an intelligent furniture network for human posture and activity detection [27]. Freitas et al proposed and implemented a monitoring system of a smart home system for disabled people, including those with visual and hearing impairments, activating a warning against indoor accidents using mobiles phones and a wireless sensor network [28].…”

Section: Introductionmentioning

confidence: 99%

RFID RSS Fingerprinting System for Wearable Human Activity Recognition

et al. 2020

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Alternative healthcare solutions have been identified as a viable approach to ameliorate the increasing demand for telehealth and prompt healthcare delivery. Moreover, indoor ocalization using different technologies and approaches have greatly contributed to alternative healthcare solutions. In this paper, a cost-effective, radio frequency identification (RFID)-based indoor location system that employs received signal strength (RSS) information of passive RFID tags is presented. The proposed system uses RFID tags placed at different positions on the target body. The mapping of the analysed data against a set of reference position datasets is used to accurately track the vertical and horizontal positioning of a patient within a confined space in real-time. The Euclidean distance model achieves an accuracy of 98% for all sampled activities. However, the accuracy of the activity recognition algorithm performs below the threshold performance for walking and standing, which is due to similarities in the target height, weight and body density for both activities. The obtained results from the proposed system indicate significant potentials to provide reliable health measurement tool for patients at risk.

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Low intrusive Ehealth monitoring: human posture and activity level detection with an intelligent furniture network

Cited by 8 publications

References 10 publications

Innovative and Assistive eHealth Technologies for Smart Therapeutic and Rehabilitation Outdoor Spaces for the Elderly Demographic

Innovative and Assistive eHealth Technologies for Smart Therapeutic and Rehabilitation Outdoor Spaces for the Elderly Demographic

Design & Development of IoT Based Rehabilitation Outdoor Landscape for Gait Phase Recognition

RFID RSS Fingerprinting System for Wearable Human Activity Recognition

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