Abstract
Wearable sensors have traditionally been designed around a micro controller that periodically reads values from attached sensor chips, before analyzing and forwarding data. As many off-the-shelf sensor chips have become smaller and widespread in consumer appliances, the way they are interfaced has become digital and more potent. This paper investigates the impact of using such chips that are not only smaller and cheaper as their predecessors, but also come with an arsenal of extra processing and detection capabilities, built in the sensor package. A case study with accompanying experiments using two MEMS accelerometers, show that using these capabilities can cause significant reductions in resources for data acquisition, and could even support basic recognition tasks.
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Notes
- 1.
Leading to 100Â Hz sampling rate (as also used in e.g. [11]).
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Van Laerhoven, K., Scholl, P.M. (2016). Interrupts Become Features: Using On-Sensor Intelligence for Recognition Tasks. In: Szewczyk, R., Kaštelan, I., Temerinac, M., Barak, M., Sruk, V. (eds) Embedded Engineering Education. Advances in Intelligent Systems and Computing, vol 421. Springer, Cham. https://doi.org/10.1007/978-3-319-27540-6_12
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DOI: https://doi.org/10.1007/978-3-319-27540-6_12
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