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Article

Extraction of Lumbar Spine Motion Using a 3-IMU Wearable Cluster

1
Mechanical Engineering, College of Engineering, San Diego State University, San Diego, CA 92182, USA
2
Doctor of Physical Therapy Program, School of Exercise and Nutritional Sciences, San Diego State University, San Diego, CA 92182, USA
3
Electrical and Computer Engineering, College of Engineering, San Diego State University, San Diego, CA 92182, USA
*
Author to whom correspondence should be addressed.
Sensors 2023, 23(1), 182; https://doi.org/10.3390/s23010182
Submission received: 22 November 2022 / Revised: 17 December 2022 / Accepted: 20 December 2022 / Published: 24 December 2022
(This article belongs to the Collection Sensors for Gait, Posture, and Health Monitoring)

Abstract

Spine movement is a daily activity that can indicate health status changes, including low back pain (LBP) problems. Repetitious and continuous movement on the spine and incorrect postures during daily functional activities may lead to the potential development and persistence of LBP problems. Therefore, monitoring of posture and movement is essential when designing LBP interventions. Typically, LBP diagnosis is facilitated by monitoring upper body posture and movement impairments, particularly during functional activities using body motion sensors. This study presents a fully wireless multi-sensor cluster system to monitor spine movements. The study suggests an attempt to develop a new method to monitor the lumbopelvic movements of interest selectively. In addition, the research employs a custom-designed robotic lumbar spine simulator to generate the ideal lumbopelvic posture and movements for reference sensor data. The mechanical motion templates provide an automated sensor pattern recognition mechanism for diagnosing the LBP.
Keywords: wearable biomedical sensors; wireless network; medical equipment; multi-sensor fusion; inertial measurement unit; robotic simulator; low back pain; body kinematics; body area network (BAN) wearable biomedical sensors; wireless network; medical equipment; multi-sensor fusion; inertial measurement unit; robotic simulator; low back pain; body kinematics; body area network (BAN)

Share and Cite

MDPI and ACS Style

Moon, K.S.; Gombatto, S.P.; Phan, K.; Ozturk, Y. Extraction of Lumbar Spine Motion Using a 3-IMU Wearable Cluster. Sensors 2023, 23, 182. https://doi.org/10.3390/s23010182

AMA Style

Moon KS, Gombatto SP, Phan K, Ozturk Y. Extraction of Lumbar Spine Motion Using a 3-IMU Wearable Cluster. Sensors. 2023; 23(1):182. https://doi.org/10.3390/s23010182

Chicago/Turabian Style

Moon, Kee S., Sara P. Gombatto, Kim Phan, and Yusuf Ozturk. 2023. "Extraction of Lumbar Spine Motion Using a 3-IMU Wearable Cluster" Sensors 23, no. 1: 182. https://doi.org/10.3390/s23010182

APA Style

Moon, K. S., Gombatto, S. P., Phan, K., & Ozturk, Y. (2023). Extraction of Lumbar Spine Motion Using a 3-IMU Wearable Cluster. Sensors, 23(1), 182. https://doi.org/10.3390/s23010182

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