Inertial sensor-based step length estimation model by means of principal component analysis

Melanija Vezočnik (Author), Roman Kamnik (Author), Matjaž B. Jurič (Author)

Abstract

Inertial sensor-based step length estimation has become increasingly important with the emergence of pedestrian-dead-reckoning-based (PDR-based) indoor positioning. So far, many refined step length estimation models have been proposed to overcome the inaccuracy in estimating distance walked. Both the kinematics associated with the human body during walking and actual step lengths are rarely used in their derivation. Our paper presents a new step length estimation model that utilizes acceleration magnitude. To the best of our knowledge, we are the first to employ principal component analysis (PCA) to characterize the experimental data for the derivation of the model. These data were collected from anatomical landmarks on the human body during walking using a highly accurate optical measurement system. We evaluated the performance of the proposed model for four typical smartphone positions for long-term human walking and obtained promising results: the proposed model outperformed all acceleration-based models selected for the comparison producing an overall mean absolute stride length estimation error of 6.44 cm. The proposed model was also least affected by walking speed and smartphone position among acceleration-based models and is unaffected by smartphone orientation. Therefore, the proposed model can be used in the PDR-based indoor positioning with an important advantage that no special care regarding orientation is needed in attaching the smartphone to a particular body segment. All the sensory data acquired by smartphones that we utilized for evaluation are publicly available and include more than 10 h of walking measurements.

Keywords

model hoje;inercijski senzorji;javna podatkovna množica;pametni telefon;model za oceno dolžine koraka;gait model;inertial sensors;open-source dataset;smartphone;step length estimation model;

Data

Language:	English
Year of publishing:	2021
Typology:	1.01 - Original Scientific Article
Organization:	UL FRI - Faculty of Computer and Information Science
UDC:	681.586:004.382.745
COBISS:	64014851
ISSN:	1424-8220
Views:	120
Downloads:	44
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	model hoje;inercijski senzorji;javna podatkovna množica;pametni telefon;model za oceno dolžine koraka;
Type (COBISS):	Article
Pages:	str. 1-22
Volume:	ǂVol. ǂ21
Issue:	ǂno. ǂ10
Chronology:	May 2021
DOI:	10.3390/s21103527
ID:	14759907