Exercise repetition detection for resistance training based on smartphones

Igor Pernek (Avtor), Karin Anna Hummel (Avtor), Peter Kokol (Avtor)

Povzetek

Regular exercise is one of the most important factors in maintaining a good state of health. In the past, different systems have been proposed to assist people when exercising. While most of those systems focus only on cardio exercises such as running and cycling, we exploit smartphones to support leisure activities with a focus on resistance training. We describe how off-the-shelf smartphones without additional external sensors can be leveragedto capture resistance training data and to give reliable training feedback. We introduce a dynamic time warping-based algorithm to detect individual resistance training repetitions from the smartphoneʼs acceleration stream. We evaluate the algorithm in terms of the number of correctly recognized repetitions. Additionally, for providing feedback about the qualityof repetitions, we use the duration of an individual repetition and analyze how accurately start and end times of repetitions can be detected by our algorithm. Our evaluations are based on 3,598 repetitions performed by tenvolunteers exercising in two distinct scenarios, a gym and a natural environment. The results show an overall repetition miscount rate of about 1 %and overall temporal detection error of about 11 % of individual repetition duration.

Ključne besede

wearable systems;resistance training;smartphone;accelerometer;

Podatki

Jezik:	Angleški jezik
Leto izida:	2012
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	UM FZV - Fakulteta za zdravstvene vede
UDK:	621.39:004
COBISS:	1867684
ISSN:	1617-4909
Št. ogledov:	1203
Št. prenosov:	87
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Angleški jezik
URN:	URN:SI:UM:
Vrsta dela (COBISS):	Delo ni kategorizirano
Strani:	str. 781-782
Letnik:	ǂVol. ǂ17
Zvezek:	ǂiss. ǂ4
Čas izdaje:	apr. 2013
DOI:	10.1007/s00779-012-0626-y
ID:	1437325