• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.345-352
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• 2012

Objective: The aim of this study is to evaluate the accuracy and reliability of Spine-Pelvis Monitor(SPM) that was developed to measure 3-dimensional motion of spine and pelvis using tilt sensor and gyro sensor. Background: The main cause of low back pain is very much associated with the task using the low back and pelvis, but no measurement technique can quantify the both spine and pelvis. Method: For testing the SPM, 125 angles from three anatomical planes were measured three times in order to evaluate the accuracy and reliability. The accuracy of SPM in measuring dynamic motion was evaluated using digital motion analysis system. The motion pattern captured by two measuring methods was compared with each other. In result, the percentage error and Cronbach coefficient alpha were calculated to evaluate the accuracy and reliability. Results: The percentage error was 0.35% in flexion-extension on sagittal plane, 0.43% in lateral bending on coronal plane, and 0.40% in twisting on transverse plane. The Cronbach coefficient alpha was 1.00, 0.99 and 0.99 in sagittal, coronal and transvers plane, respectively. Conclusion: The SPM showed less than 1% error for static measurement, and showed reasonably similar pattern with the digital motion system. Application: The results of this study showed that the SPM can be the measuring method of spine pelvis motion that enhances the kinematic analysis of low back dynamics.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.82-89
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• 2023

Due to the characteristics of ship structure, the compartment structure is complicated and narrow, so safety accidents frequently occur during the work process. The main causes of accidents include structural collisions, falling objects, toxic substance leaks, fires, explosions, asphyxiation, and more. Understanding the on-site conditions of workers during accidents is crucial for mitigating damages. In order to ensure safety, the on-site situation is monitored using CCTV in the ship, but it is difficult to prevent accidents with the existing method. To address this issue, a smart safety helmet equipped with location identification and voice/video communication capabilities is being developed as a safety technology. Additionally, the smart safety helmet incorporates environmental sensors for temperature, humidity, vibration, noise, tilt (gyro sensor), and gas detection within the work area. These sensors can notify workers wearing the smart safety helmet of hazardous situations. By utilizing the smart safety helmet and environmental sensors, the safety of workers aboard ships can be enhanced.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.29-39
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• 2015

This paper describes a design and implementation of fuzzy-based algorithm for hand-shake state detection and error compensation in the mobile optical image stabilization(OIS) motion detector. Since the gyro sensor output of the OIS motion detector includes inherent error signals, accurate error correction is required for prompt hand-shake error compensation and stable hand-shake state detection. In this research with a little computation overhead of fuzzy-based algorithm, the hand-shake error compensation could be improved by quickly reducing the angle and phase error for the hand-shake frequencies. Further, stability of the OIS system could be enhanced by the hand-shake states of {Halt, Little vibrate, Big vibrate, Pan/Tilt}, classified by subdividing the hand-shake angle. The performance and stability of the proposed algorithm in OIS motion detector is quantitatively and qualitatively evaluated with the emulated hand-shaking of ${\pm}0.5^{\circ}$, ${\pm}0.8^{\circ}$ vibration and 2~12Hz frequency. In experiments, the average error compensation gain of 3.71dB is achieved with respect to the conventional BACF/DCF algorithm; and the four hand-shake states are detected in a stable manner.