Extraction of Shoulder Parts to Avoid Heavy Load Based on Pain while Walking with Backpack

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When using a backpack, proper shoulder load reduction is required. We focused on pain (nociceptive pain), which is a warning signal to protect the human body, and we aimed to extract the shoulder parts to avoid heavy loads while walking with a backpack. We set 19 measuring points on each shoulder and 12 measuring points on the lower back. Using three-axis tactile sensors, we then recorded the interface load on the shoulders and lower back under two back panel conditions: general flat panel and panel with lumbar pad. With 180 data for mean load and 150 data for peak load on each measuring point, we confirmed the load distribution and load shift effects using a lumbar pad by comparing the shoulder load and the lower back load. Then, the shoulder load data was normalized by the pain threshold for a single-point pressure stimulus at each measuring point of the subject. The pain threshold was estimated by an approximate expression with a sigmoid function for pain scores, which were collected by subjective evaluation with a pain scale. In statistical analysis, through multiple comparisons (Steel-Dwass test) for the mean values of the normalized shoulder load on each measuring point and its mean value of the entire shoulder, we extracted seven potential high-risk points (coracoid process, medial and lateral part of the clavicle regions, medial and lateral part of the ridgeline of the shoulder, and supraspinatus). Moreover, we observed that high-risk loads remained locally behind a significant reduction of the entire shoulder load with a lumbar pad. These results can be used to improve backpack design for proper loads on the shoulder.

Original languageEnglish
Title of host publication2021 IEEE/SICE International Symposium on System Integration, SII 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages357-362
Number of pages6
ISBN (Electronic)9781728176581
DOIs
Publication statusPublished - 2021 Jan 11
Event2021 IEEE/SICE International Symposium on System Integration, SII 2021 - Virtual, Iwaki, Fukushima, Japan
Duration: 2021 Jan 112021 Jan 14

Publication series

Name2021 IEEE/SICE International Symposium on System Integration, SII 2021

Conference

Conference2021 IEEE/SICE International Symposium on System Integration, SII 2021
Country/TerritoryJapan
CityVirtual, Iwaki, Fukushima
Period21/1/1121/1/14

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Information Systems and Management
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

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