Fall detection and activity monitoring system using dynamic time warping for elderly and disabled people

Paiyarom, Sasiwan; Tangamchit, Poj; Keinprasit, Rachaporn; Kayasith, Prakasith

doi:10.1145/1592700.1592711

Cited by 6 publications

(1 citation statement)

References 5 publications

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“…In a speech waveform, the duration of each spoken sound and the interval between sounds can vary, but the overall speech waveforms must have a similar “shape”. In addition to speech recognition, DTW has also been found useful in many other disciplines, including, gesture recognition [3], robotics [4], manufacturing [5], and health monitoring [6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Efficient Kernel-Based Subsequence Search for Enabling Health Monitoring Services in IoT-Based Home Setting

Candelieri

Fedorov

Messina

2019

Sensors

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This paper presents an efficient approach for subsequence search in data streams. The problem consists of identifying coherent repetitions of a given reference time-series, also in the multivariate case, within a longer data stream. The most widely adopted metric to address this problem is Dynamic Time Warping (DTW), but its computational complexity is a well-known issue. In this paper, we present an approach aimed at learning a kernel approximating DTW for efficiently analyzing streaming data collected from wearable sensors, while reducing the burden of DTW computation. Contrary to kernel, DTW allows for comparing two time-series with different length. To enable the use of kernel for comparing two time-series with different length, a feature embedding is required in order to obtain a fixed length vector representation. Each vector component is the DTW between the given time-series and a set of “basis” series, randomly chosen. The approach has been validated on two benchmark datasets and on a real-life application for supporting self-rehabilitation in elderly subjects has been addressed. A comparison with traditional DTW implementations and other state-of-the-art algorithms is provided: results show a slight decrease in accuracy, which is counterbalanced by a significant reduction in computational costs.

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Section: Introductionmentioning

confidence: 99%

Efficient Kernel-Based Subsequence Search for Enabling Health Monitoring Services in IoT-Based Home Setting

Candelieri

Fedorov

Messina

2019

Sensors

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Fall Detection with Orientation Calibration Using a Single Motion Sensor

Shuo

Chen

2017

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Fall detection with body-worn sensors

et al. 2013

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Limited methodological agreement between sensor-based fall detection studies using body-worn sensors was identified. Published evidence-based support for commercially available fall detection devices is still lacking. A worldwide research group consensus is needed to address fundamental issues such as incident verification, the establishment of guidelines for fall reporting and the development of a common fall definition.

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Fall detection and activity monitoring system using dynamic time warping for elderly and disabled people

Cited by 6 publications

References 5 publications

Efficient Kernel-Based Subsequence Search for Enabling Health Monitoring Services in IoT-Based Home Setting

Efficient Kernel-Based Subsequence Search for Enabling Health Monitoring Services in IoT-Based Home Setting

Fall Detection with Orientation Calibration Using a Single Motion Sensor

Fall detection with body-worn sensors

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