Design and Ergonomics of Monitoring System for Elderly

Andreoni, Giuseppe; Costa, Fiammetta; Attanasio, Alberto; Baroni, Giuseppe; Muschiato, Sabrina; Nonini, Paola; Pagni, Andrea; Biraghi, Roberto; Pozzi, Roberto; Romero, Marcelo; Perego, Paolo

doi:10.1007/978-3-319-07725-3_49

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Within research there has been a corresponding increase in studies developing and using sensors in areas such as healthcare and activity monitoring, e.g. [1]- [5]. Like many others we believe that the potential of on-body sensing is significant.…”

Section: Introductionmentioning

confidence: 94%

Inductive Power Transfer for On-body Sensors. Defining a design space for safe, wirelessly powered on-body health sensors.

Worgan

Clare

Proynov

et al. 2015

Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare

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Designers of on-body health sensing devices face a difficult choice. They must either minimise the power consumption of devices, which in reality means reducing the sensing capabilities, or build devices that require regular battery changes or recharging. Both options limit the effectiveness of devices. Here we investigate an alternative. This paper presents a method of designing safe, wireless, inductive power transfer into on-body sensor products. This approach can produce sensing devices that can be worn for longer durations without the need for human intervention, whilst also having greater sensing and data capture capabilities. The paper addresses significant challenges in achieving this aim, in particular: device safety, sufficient power transfer, and human factors regarding device geometry. We show how to develop a device that meets stringent international safety guidelines for electromagnetic energy on the body and describe a design space that allows designers to make trade-offs that balance power transfer with other constraints, e.g. size and bulk, that affect the wearability of devices. Finally we describe a rapid experimental method to investigate the optimal placement of on-body devices and the actual versus theoretical power transfer for on-body, inductively powered devices.

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Section: Introductionmentioning

confidence: 94%

Inductive Power Transfer for On-body Sensors. Defining a design space for safe, wirelessly powered on-body health sensors.

Worgan

Clare

Proynov

et al. 2015

Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare

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“…Falls are one of the most hazardous scenarios [1], [2]. Approximately 33 % (range: 15 % to 44.9 %) of elderly community-dwelling persons in the USA are older than 65 years, and up to 60 % of nursing home residents fall each year [3]- [5]. Falls (loss of balance resulting in coming to rest on the floor) are the one of the major causes of injuries resulting in death and of injury-related hospitalization among senior citizens.…”

Section: Introductionmentioning

confidence: 99%

“…Different works have focused on the possibility of detecting a fall using portable systems [5]- [24]. The majority of the methods rely on wearable sensors [7]- [10] and vision techniques [11]- [18].…”

Section: Introductionmentioning

confidence: 99%

Automatic fall monitoring using the floor vibration

Tarabini

Gocanin

Saggin³

et al. 2019

ACTA IMEKO

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<span lang="EN-GB">This work investigates the possibility of monitoring the activity and the falls of people in dwellings using three or more accelerometers fixed on the ground. The main difference between the proposed method and existing ones is the use of acceleration to estimate the impact force by using the apparent mass of the floor; the latter is experimentally identified in each room in which the tests were performed using the heel drop test. The study has two parts: 1. the apparent masses of different dwellings’ floors have been measured. 2. the ground reaction force is studied using a purposely designed force platform with a surface of approximately 2 m x 1 m. The force platform allowed the measurement of the forces generated by the falls of 21 subjects, of a crash test dummy (falling in front or rear direction from seated and standing position, with or without the interposition of objects on the trajectory), and of common objects (e.g. dishes, water bottles, books). The impact location is estimated by triangulation, using a wavelet algorithm derived from the existent literature. The results show the possibility of identifying the presence of subjects inside the room and the fall of subjects in the majority of dwellings. We conclude that the proposed method allows a clear distinction between the fall of subjects and objects, given that the difference in terms of force (which is estimated from the floor’s apparent mass and from the measured acceleration) is at least of one order of magnitude.</span>

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