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2018, vol. 28, iss. 28, pp. 135-143
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New method for human activity recognition based on IMU sensors and digital speech processing theory
Nova metoda za prepoznavanje aktivnosti ljudi zasnovana na IMU senzorima i na teoriji digitalne obrade govora
aUniversity of Belgrade, Faculty of Electrical Engineering + University of Belgrade, Electrical Engineering Institute 'Nikola Tesla' bUniversity of Belgrade, Electrical Engineering Institute 'Nikola Tesla'
email: nikolacakic@ieent.org
Keywords: human activity recognition; short-time log energy; cumulative sum; activity state detection; IMU sensors; physical exercises
Ključne reči: prepoznavanje aktivnosti ljudi; kratkotrajni logaritam energije; kumulativna suma; detekcija stanja aktivnosti; IMU senzori; fizičke vežbe
Abstract
This paper presents a new method for human activity recognition (HAR). Nowadays the biggest parts of HAR systems are relying on wearable IMU (inertial measurement unit) sensors. The common IMU sensors are accelerometers and gyroscopes. These sensors are widespread in mobile devices such as smartphones and smart watches. Authors usually use real time signal features as inputs for classifiers that are calculated using sliding windows only. This paper proposes a new method based on speech-silence discrimination technique for detecting the beginning and the end of an activity. The presented method relies on short-time log energy (STLE) and cumulative sum of angle of STLE values. The method was tested on two similar physical activities: squat and knee raise. This algorithm provides a 41.2% pre-classification accuracy, by precise detection of the length of individual exercise states (start, intermediate, and finish position) only. The proposed method reduces complexity, classifying only activities when they are detected (not classifying pause between activities).
Sažetak
U radu je prezentovana nova metoda za prepoznavanje aktivnosti ljudi (HAR). U današnje vreme najveći delovi HAR sistema se oslanjaju na inercijalne IMU senzore podesne za nošenje. Najzastupljeniji IMU senzori su akcelerometar i žiroskop. Pomenuti senzori su široko rasprostranjeni u mobilnim uređajima kao što su pametni telefoni ili pametni satovi. Autori obično koriste karakteristične vrednosti signala u realnom vremenu kao ulaze u klasifikator računajući ih samo pomoću sliding prozora. Ovaj rad predlaže novu metodu zasnovanu na speech-silence diskriminacionoj tehnici za detektovanje početka i kraja određene aktivnosti. Predstavljena metoda se oslanja na kratkotrajni logaritam energije (STLE) i kumulativnu sumu ugla STLE. Metoda je testirana na dve slične fizičke vežbe: čučanj i podizanje kolena. Ovaj algoritam obezbeđuje pre klasifikacionu preciznost od 41,2%, samo na osnovu precizne detekcije dužine pojedinih stanja vežbe (start, srednji i krajnji položaj). Predložena metoda smanjuje kompleksnost, klasifikovajući aktivnosti samo kada se detektuju (ne klasifikujući pauze između aktivnosti).
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References
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