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

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

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.

• Language: English
• Keywords: gait model, inertial sensors, open-source dataset, smartphone, step length estimation model
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science ; FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2021
• Number of pages: 22 str.
• Numbering: Vol. 21, iss. 10, art. 3527
• PID: 20.500.12556/RUL-135443
• UDC: 681.586:004.382.745
• ISSN on article: 1424-8220
• DOI: 10.3390/s21103527
• COBISS.SI-ID: 64014851
• Publication date in RUL: 15.03.2022

Record is a part of a journal

• Title: Sensors
• Shortened title: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 19.05.2021

Secondary language

• Language: Slovenian
• Keywords: model hoje, inercijski senzorji, javna podatkovna množica, pametni telefon, model za oceno dolžine koraka