Data quality oriented taxonomy of ambient assisted living systems

Beevi, Femina Hassan Aysha; Wagner, Stefan; Hallerstede, Stefan; Pedersen, Christian Fischer

doi:10.1049/ic.2015.0140

Cited by 6 publications

(2 citation statements)

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“…The first type of these floor sensors measures the impedance of electric field couplings for an array of sensor plates, which is also called near field imaging [33]. A second type measures the electric capacitance, like the ELSI ® Smart Floor by Mari Mils [34,35], or SensFloor ® by Future-Shape [3,[36][37][38][39][40][41][42][43]. The latter one was used for the data acquisition here, and is described in more detail later-on.…”

Section: Sensors For Gait and Behaviour Analysismentioning

confidence: 99%

Detecting Walking Challenges in Gait Patterns Using a Capacitive Sensor Floor and Recurrent Neural Networks

Hoffmann

Brodowski

Steinhage³

et al. 2021

Sensors

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Gait patterns are a result of the complex kinematics that enable human two-legged locomotion, and they can reveal a lot about a person’s state and health. Analysing them is useful for researchers to get new insights into the course of diseases, and for physicians to track the progress after healing from injuries. When a person walks and is interfered with in any way, the resulting disturbance can show up and be found in the gait patterns. This paper describes an experimental setup for capturing gait patterns with a capacitive sensor floor, which can detect the time and position of foot contacts on the floor. With this setup, a dataset was recorded where 42 participants walked over a sensor floor in different modes, inter alia, normal pace, closed eyes, and dual-task. A recurrent neural network based on Long Short-Term Memory units was trained and evaluated for the classification task of recognising the walking mode solely from the floor sensor data. Furthermore, participants were asked to do the Unilateral Heel-Rise Test, and their gait was recorded before and after doing the test. Another neural network instance was trained to predict the number of repetitions participants were able to do on the test. As the results of the classification tasks turned out to be promising, the combination of this sensor floor and the recurrent neural network architecture seems like a good system for further investigation leading to applications in health and care.

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Section: Sensors For Gait and Behaviour Analysismentioning

confidence: 99%

Detecting Walking Challenges in Gait Patterns Using a Capacitive Sensor Floor and Recurrent Neural Networks

Hoffmann

Brodowski

Steinhage³

et al. 2021

Sensors

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show abstract

“… [ 45 ] S21 Disseminating ambient assisted living in rural areas Leitner, G., Felfernig, A., Fercher, A.J., and Hitz, M. [ 46 ] S22 A cloud-based Internet of Things platform for ambient assisted living Cubo, J., Nieto, A., and Pimentel, E. [ 47 ] S23 Active in-database processing to support ambient assisted living systems De Morais, W.O., Lundström, J., and Wickström, N. [ 48 ] S24 Authentication protocol for an ambient assisted living system He, D., and Zeadally, S. [ 49 ] S25 Challenges in designing and implementation of an effective ambient assisted living system Koleva, P., Tonchev, K., Balabanov, G., Manolova, A., and Poulkov, V. [ 50 ] S26 Data quality oriented taxonomy of ambient assisted living systems Beevi, F.A., Wagner, S., Hallerstede, S., and Pedersen, C.F. [ 51 ] S27 A new approach of facial expression recognition for ambient assisted living Yaddaden, Y., Bouzouane, A., Adda, M., and Bouchard, B. [ 52 ] S28 Expanding the Coverage of Ambient Assisted Living Systems Bentes, J., Trevisan, D., and Viterbo, J.…”

Section: Table A1mentioning

confidence: 99%

Barriers and Facilitators of Ambient Assisted Living Systems: A Systematic Literature Review

Márquez

Taramasco

2023

IJERPH

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Ambient Assisted Living Systems (AALSs) use information and communication technologies to support care for the growing population of older adults. AALSs focus on providing multidimensional support to families, primary care facilities, and patients to improve the quality of life of the elderly. The literature has studied the qualities of AALSs from different perspectives; however, there has been little discussion regarding the operational experience of developing and deploying such systems. This paper presents a literature review based on the PRISMA methodology regarding operational facilitators and barriers of AALSs. This study identified 750 papers, of which 61 were selected. The results indicated that the selected studies mentioned more barriers than facilitators. Both barriers and facilitators concentrate on aspects of developing and configuring the technological infrastructure of AALSs. This study organizes and describes the current literature on the challenges and opportunities regarding the operation of AALSs in practice, which translates into support for practitioners when developing and deploying AALSs.

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