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Open AccessArticle

Design and Validation of a Minimal Complexity Algorithm for Stair Step Counting

Dipartimento di Informatica, Università degli Studi di Milano, Via Giovanni Celoria 18, 20133 Milan, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, via Golgi 39, 20133 Milan, Italy
Istituto di Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, via Fratelli Cervi 93, 20090 Segrate (MI), Italy
Dipartimento di Medicina Molecolare, Università degli Studi di Pavia, Via Forlanini 14, 27100 Pavia, Italy
Flex Design srl, Via Ernesto Breda 176, 20126 Milan, Italy
Author to whom correspondence should be addressed.
Computers 2020, 9(2), 31;
Received: 20 March 2020 / Revised: 10 April 2020 / Accepted: 12 April 2020 / Published: 16 April 2020
Wearable sensors play a significant role for monitoring the functional ability of the elderly and in general, promoting active ageing. One of the relevant variables to be tracked is the number of stair steps (single stair steps) performed daily, which is more challenging than counting flight of stairs and detecting stair climbing. In this study, we proposed a minimal complexity algorithm composed of a hierarchical classifier and a linear model to estimate the number of stair steps performed during everyday activities. The algorithm was calibrated on accelerometer and barometer recordings measured using a sensor platform worn at the wrist from 20 healthy subjects. It was then tested on 10 older people, specifically enrolled for the study. The algorithm was then compared with other three state-of-the-art methods, which used the accelerometer, the barometer or both. The experiments showed the good performance of our algorithm (stair step counting error: 13.8%), comparable with the best state-of-the-art (p > 0.05), but using a lower computational load and model complexity. Finally, the algorithm was successfully implemented in a low-power smartwatch prototype with a memory footprint of about 4 kB. View Full-Text
Keywords: stair step counting; human activity recognition; wearable sensors; active ageing stair step counting; human activity recognition; wearable sensors; active ageing
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Coluzzi, D.; Rivolta, M.W.; Mastropietro, A.; Porcelli, S.; Mauri, M.L.; Civiello, M.T.L.; Denna, E.; Rizzo, G.; Sassi, R. Design and Validation of a Minimal Complexity Algorithm for Stair Step Counting. Computers 2020, 9, 31.

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