Literature DB >> 19162939

Wheelchair type biomedical system with event-recorder function.

Dong-Kyoon Han1, Jong-Myoung Kim, Eun-Jong Cha, Tae-Soo Lee.   

Abstract

The present study is about a biometric system for a wheelchair, which can measure both bio-signal (ECG-Electrocardiogram, BCG-Ballistocardiogram) and kinetic signal (acceleration) simultaneously and send the data to a remote medical server. The equipment was developed with the object of building a system that measures the bio-signal and kinetic signal of a subject who is moving or at rest on a wheelchair and transmits the measured signals to a remote server through a CDMA (Code Division Multiple Access) network. The equipment is composed of body area network and remote medical server. The body area network was designed to obtain bio-signal and kinetic signal simultaneously and, on the occurrence of an event, to transmit data to a remote medical server through a CDMA network. The remote medical server was designed to display event data transmitted from the body area network in real time. The performance of the developed system was evaluated through two experiments. First, we measured battery life on the occurrence of events, and second, we tested whether biometric data are transmitted accurately to the remote server on the occurrence of an event. In the first experiment using the developed equipment, events were triggered 16 times and the battery worked stably for around 29 hours. In the second experiment, when an event took place, the corresponding data were transmitted accurately to the remote medical server through a CDMA network. This system is expected to be usable for the healthcare of those moving on a wheelchair and applicable to a mobile healthcare system.

Entities:  

Mesh:

Year:  2008        PMID: 19162939     DOI: 10.1109/IEMBS.2008.4649436

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Data collection capabilities of a new non-invasive monitoring system for patients with advanced multiple sclerosis.

Authors:  Diego E Arias; Esteban J Pino; Pablo Aqueveque; Dorothy W Curtis
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

2.  Sensor Cell Network for Pressure, Temperature and Position Detection on Wheelchair Users.

Authors:  Cátia Tavares; Daniela Real; Maria de Fátima Domingues; Nélia Alberto; Hugo Silva; Paulo Antunes
Journal:  Int J Environ Res Public Health       Date:  2022-02-15       Impact factor: 3.390

  2 in total

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