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Long-Term Activity Monitoring with a Wearable Sensor Node

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Long-Term Activity Monitoring with a Wearable Sensor Node. / Laerhoven, Kristof Van; Gellersen, Hans; Malliaris, Yanni G.
BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks. 2006. p. 171-174.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Laerhoven, KV, Gellersen, H & Malliaris, YG 2006, Long-Term Activity Monitoring with a Wearable Sensor Node. in BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks. pp. 171-174, BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks, MIT Boston, 1/01/00. https://doi.org/10.1109/BSN.2006.39

APA

Laerhoven, K. V., Gellersen, H., & Malliaris, Y. G. (2006). Long-Term Activity Monitoring with a Wearable Sensor Node. In BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks (pp. 171-174) https://doi.org/10.1109/BSN.2006.39

Vancouver

Laerhoven KV, Gellersen H, Malliaris YG. Long-Term Activity Monitoring with a Wearable Sensor Node. In BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks. 2006. p. 171-174 doi: 10.1109/BSN.2006.39

Author

Laerhoven, Kristof Van ; Gellersen, Hans ; Malliaris, Yanni G. / Long-Term Activity Monitoring with a Wearable Sensor Node. BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks. 2006. pp. 171-174

Bibtex

@inproceedings{75d3b57d8d3341f2a14247176ab32607,
title = "Long-Term Activity Monitoring with a Wearable Sensor Node",
abstract = "This paper introduces an encapsulated sensor node that is devised to monitor and record motion patterns over long, quotidian periods of time with potential application in psychological studies. Its design fuses different sensing modalities to allow efficient capturing of tilt and acceleration stimuli, as well as embedded algorithms that abstract from the raw sensory data to indicative features. By combining tilt switches and accelerometers with customized processing techniques, it is argued that a power-efficient yet information-rich approach is reached for the observation and logging of human motion-based activity.",
keywords = "cs_eprint_id, 1604 cs_uid, 382",
author = "Laerhoven, {Kristof Van} and Hans Gellersen and Malliaris, {Yanni G.}",
year = "2006",
doi = "10.1109/BSN.2006.39",
language = "English",
pages = "171--174",
booktitle = "BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks",
note = "BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks ; Conference date: 01-01-1900",

}

RIS

TY - GEN

T1 - Long-Term Activity Monitoring with a Wearable Sensor Node

AU - Laerhoven, Kristof Van

AU - Gellersen, Hans

AU - Malliaris, Yanni G.

PY - 2006

Y1 - 2006

N2 - This paper introduces an encapsulated sensor node that is devised to monitor and record motion patterns over long, quotidian periods of time with potential application in psychological studies. Its design fuses different sensing modalities to allow efficient capturing of tilt and acceleration stimuli, as well as embedded algorithms that abstract from the raw sensory data to indicative features. By combining tilt switches and accelerometers with customized processing techniques, it is argued that a power-efficient yet information-rich approach is reached for the observation and logging of human motion-based activity.

AB - This paper introduces an encapsulated sensor node that is devised to monitor and record motion patterns over long, quotidian periods of time with potential application in psychological studies. Its design fuses different sensing modalities to allow efficient capturing of tilt and acceleration stimuli, as well as embedded algorithms that abstract from the raw sensory data to indicative features. By combining tilt switches and accelerometers with customized processing techniques, it is argued that a power-efficient yet information-rich approach is reached for the observation and logging of human motion-based activity.

KW - cs_eprint_id

KW - 1604 cs_uid

KW - 382

U2 - 10.1109/BSN.2006.39

DO - 10.1109/BSN.2006.39

M3 - Conference contribution/Paper

SP - 171

EP - 174

BT - BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks

T2 - BSN '06: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks

Y2 - 1 January 1900

ER -