Implementation of a Physical Activity Monitoring System for the Elderly People with Built-in Vital Sign and Fall Detection

Dinh, Anh; Teng, Daniel; Chen, Li; Shi, Yang; McCrosky, Carl; Basran, Jenny; Bello-Hass, V. Del

doi:10.1109/itng.2009.60

Cited by 32 publications

(12 citation statements)

References 11 publications

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“…Sampling rate set to 120 Hz exceeds the characteristic response of human movement [ 49 ]. Other sampling frequencies for accelerometer data include 40 Hz [ 50 ], 16 kHz [ 51 ], 512, 76.25, 64, and 5 Hz [ 8 , 52 – 54 ].…”

Section: Sensor Placement and Data Collectionmentioning

confidence: 99%

Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations

Khusainov

Azzi

Achumba

et al. 2013

Sensors

151

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Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions.

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Section: Sensor Placement and Data Collectionmentioning

confidence: 99%

Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations

Khusainov

Azzi

Achumba

et al. 2013

Sensors

151

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“…For example, fall detection and heart rate are monitored in [53] through a wearable device wear on the chest of the person consisting of a tri-axial accelerometer, a two-axis gyroscope and a heartbeat detection circuit. The wearable device detects and sends signals using ZigBee.…”

Section: Human Activity Monitoringmentioning

confidence: 99%

Application specific study, analysis and classification of body area wireless sensor network applications

et al. 2015

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“…The wearable computing requires users to wear special material that is embedded with an array of sensors [11][12][13][14]. These different sensors may increase the efficiency of the system.…”

Section: Wearable Computing Projectsmentioning

confidence: 99%

Fall detection prototype for Thai elderly in mobile computing era

Kaenampornpan

Anuchad

Supaluck

2011

The 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thai

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In Thailand, it is very common for people to own at least one mobile phone. This is also the case for elderly people.They tend to feel that mobile phone is necessary for their safety and convenient in everyday living. This paper discusses our mobile application that is aimed to support independent living for the Thai elderly. Falls in the elderly people often cause serious physical injury such as fracture, cerebral hemorrhaging or even death. To be able to detect falls as early as possible is a very important method in rescuing the subjects and to facilitate the rehabilitation in the future. In this paper, we use a tri -axial accelerometer that is embedded in the mobile phone to monitor the movements of human body. The application also supports children and caters so that they are being notified when the fall is detected. As a result, they are also able to show their care and love to the elderly at the right time. We proposed a thresholdbased concept to be applied to the changes of the parameters from the tri -axial accelerometer. The results show that this application can detect the falls and notify children and care takers of the elderly effectively.

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Implementation of a Physical Activity Monitoring System for the Elderly People with Built-in Vital Sign and Fall Detection

Cited by 32 publications

References 11 publications

Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations

Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations

Application specific study, analysis and classification of body area wireless sensor network applications

Fall detection prototype for Thai elderly in mobile computing era

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