Comparative Analysis of Force-Sensitive Resistors and Triaxial Accelerometers for Sitting Posture Classification

Zhuofu Liu; Zihao Shu; Vincenzo Cascioli; Peter McCarthy

doi:10.3390/s24237705

Back

Comparative Analysis of Force-Sensitive Resistors and Triaxial Accelerometers for Sitting Posture Classification

Journal article

Open access

Peer reviewed

Comparative Analysis of Force-Sensitive Resistors and Triaxial Accelerometers for Sitting Posture Classification

Zhuofu Liu, Zihao Shu, Vincenzo Cascioli and Peter McCarthy

Sensors (Basel, Switzerland), Vol.24(23), 7705

2024

DOI: https://doi.org/10.3390/s24237705

PMID: 39686242

Files and links (1)

pdf

Published5.80 MBDownload View

CC BY V4.0, Open Access

Abstract

Accelerometers

Anticoagulants

Back pain

Data smoothing

Data transmission

Measurement techniques

Musculoskeletal diseases

Posture

Sensors

Universal Serial Bus

Sedentary behaviors, including poor postures, are significantly detrimental to health, particularly for individuals losing motion ability. This study presents a posture detection system utilizing four force-sensitive resistors (FSRs) and two triaxial accelerometers selected after rigorous assessment for consistency and linearity. We compared various machine learning algorithms based on classification accuracy and computational efficiency. The k-nearest neighbor (KNN) algorithm demonstrated superior performance over Decision Tree, Discriminant Analysis, Naive Bayes, and Support Vector Machine (SVM). Further analysis of KNN hyperparameters revealed that the city block metric with K = 3 yielded optimal classification results. Triaxial accelerometers exhibited higher accuracy in both training (99.4%) and testing (99.0%) phases compared to FSRs (96.6% and 95.4%, respectively), with slightly reduced processing times (0.83 s vs. 0.85 s for training; 0.51 s vs. 0.54 s for testing). These findings suggest that, apart from being cost-effective and compact, triaxial accelerometers are more effective than FSRs for posture detection.

Details

Title: Comparative Analysis of Force-Sensitive Resistors and Triaxial Accelerometers for Sitting Posture Classification
Authors/Creators: Zhuofu Liu - Harbin University of Science and Technology
Zihao Shu
Vincenzo Cascioli - Murdoch University
Peter McCarthy - University of South Wales
Publication Details: Sensors (Basel, Switzerland), Vol.24(23), 7705
Publisher: MDPI AG
Number of pages: 14
Grant note: Harbin University of Science and Technology: 8402/217045088 Young Elite Research Program of Harbin University of Science and Technology: F201421 Natural Science Foundation of Heilongjiang Province
This work was supported by the Young Elite Research Program of Harbin University of Science and Technology (8402/217045088) and the Natural Science Foundation of Heilongjiang Province (F201421).
Identifiers: 991005726581107891
Murdoch Affiliation: Murdoch University
Language: English
Resource Type: Journal article

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Source: InCites

Metrics

17 Record Views

1 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration; International collaboration
Citation topics: 1 Clinical & Life Sciences; 1.129 Back pain; 1.129.98 Low Back Pain
Web Of Science research areas: Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation
ESI research areas: Chemistry