Janez Podobnik (Avtor), David Kraljić (Avtor), Matjaž Zadravec (Avtor), Marko Munih (Avtor)

Povzetek

Estimation of the centre of pressure (COP) is an important part of the gait analysis, for example, when evaluating the functional capacity of individuals affected by motor impairment. Inertial measurement units (IMUs) and force sensors are commonly used to measure gait characteristic of healthy and impaired subjects. We present a methodology for estimating the COP solely from raw gyroscope, accelerometer, and magnetometer data from IMUs using statistical modelling. We demonstrate the viability of the method using an example of two models: a linear model and a non-linear Long-Short-Term Memory (LSTM) neural network model. Models were trained on the COP ground truth data measured using an instrumented treadmill and achieved the average intra-subject root mean square (RMS) error between estimated and ground truth COP of 12.3 mm and the average inter-subject RMS error of 23.7 mm which is comparable or better than similar studies so far. We show that the calibration procedure in the instrumented treadmill can be as short as a couple of minutes without the decrease in our model performance. We also show that the magnetic component of the recorded IMU signal, which is most sensitive to environmental changes, can be safely dropped without a significant decrease in model performance. Finally, we show that the number of IMUs can be reduced to five without deterioration in the model performance.

Ključne besede

analiza hoje;inercialna merilna enota;modeli hoje;ocena prijemališča sile;nevronske mreže;nosljivi senzorji;gait analysis;inertial measurement units;gait model;estimation of centre of pressure;artificial neural networks;wearable sensors;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FE - Fakulteta za elektrotehniko
UDK: 681.586
COBISS: 34924291 Povezava se bo odprla v novem oknu
ISSN: 1424-8220
Št. ogledov: 160
Št. prenosov: 52
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: analiza hoje;inercialna merilna enota;modeli hoje;ocena prijemališča sile;nevronske mreže;nosljivi senzorji;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-20
Letnik: ǂiss. ǂ21
Zvezek: 6136
Čas izdaje: Nov.-1 2020
DOI: 10.3390/s20216136
ID: 14373100