December 2019

JICE 2019 December

Showing all 5 results

  • A Game-based Upper Limb AROM Measurement System for Older Adults


    Abstract:  At present, the aging problem is becoming more and more serious, which undoubtedly causes people’s attention to the life quality of the elderly. Active range of motion (AROM) is an important index to judge the ability of daily functional activities of the elderly. Therefore, it is very important to obtain the AROM data of the elderly quickly and accurately. The traditional method of measuring the range of motion (ROM) is to measure the passive range of motion (PROM) with a goniometer by nurses, which cannot accurately reflect the elderly’s active ability in the daily life. In order to overcome the shortcomings of traditional methods, the AROM measurement system has been developed. However, in the current AROM measurement system, the elderly is guided to several specific postures, ignoring the positive role of interest in stimulating the elderly to participate in ROM measurement. In this paper, we propose a game-based upper limb AROM measurement system. In the system, the joint coordinates of the player are measured by the depth image sensor, and the AROM is calculated automatically and objectively by using the coordinates. From the experimental results, the average flection value measured by our system is 21.6 degrees larger than that measured by the goniometer. The average abduction value measured by our system is 24.1 degrees larger than that measured by goniometer. This result means that the elderly can stretch better through a game in our measurement system. In order to encourage the elderly to participate more in the game, a questionnaire survey was conducted on the elderly’s views of the game. From the analysis results, we find that the merit factor and design factor of the game have a great impact on the players’ experience in the game. The research results provide us with ideas for the improvement of the measurement system in the

  • Model for Non-contact Blood Pressure Measurement Using the Facial Feature Amount based on Amplitude and Phase Analysis


    Abstract:  To monitor the daily blood pressure, developing a non-contact method for measuring blood pressure is necessary. In a previous study, we proposed a novel method that described the vascular structure of an entire human face as an electric circuit based on amplitude and phase analyses using visible and thermal images of the face. However, the model developed by that method did not consider the order of blood flow because the model applied at random the extracted features. In the present study, it considers a model that incorporates the order of blood flow utilizing amplitude and phase analyses. As a result, the estimated accuracy is improved by considering the order of blood flow. Higher accuracy requires more detailed vascular structure information of the face. It concluded that the facial feature, which is related to the blood pressure, can be obtained by the CEOF analysis.

  • Construction of an individual model for estimating blood pressure using independent components of facial skin temperature considering time variation


    Abstract:  The objective of this study was to construct an individual model for estimating blood pressure (BP) using independent components of facial skin temperature considering time variation. In our previous study, an individual model was constructed for estimating BP by applying independent component analysis to facial skin temperature of each subject. However, in this previous study, time variations in facial skin temperature were not considered. Facial skin temperature is assumed to be related to blood flow over time as blood helps in transporting heat in the body. Therefore, the accuracy of the BP estimation model can be expected to improve if the variation of facial skin temperature caused by blood flow over time considered in addition to only the facial skin temperature. Consequently, the accuracy of the proposed model with the aforementioned considerations was found to be better than that of without these considerations. Therefore, the BP was accurately estimated using the proposed approach.  

  • Research on Gesture Based on GA – SVM


    Abstract:  Surface electromyography (sEMG) is a kind of weak electrical signal generated by muscle activity, which contains information of gesture and is widely used in prosthetic control, rehabilitation and medical treatment. The difference between different motion patterns can be reflected by the different sEMG characteristics, so the recognition of human motion can be studied. Four time-domain features including absolute mean value, waveform length, zero-crossing number and root mean square value were extracted from the double Myo arm-ring data set in Ninapro benchmark database. Classification and identification were performed by using the Support Vector Machine (SVM) optimized by Genetic Algorithms (GA). Experimental results showed that the optimized SVM classification had a better effect.

  • Effects of Daily Life Behavior with a Secondary Task on Performance and Psychophysiological States


    Abstract: The objective of this study was to evaluate the effect of daily life behavior with a secondary task on performance and psychophysiological states. The experiments were based on two conditions: dishwashing (Control) only, and dishwashing while listening to favorite music (Favorite). In the present study, statistical evaluation was conducted to assess the performance and psychophysiological states between the Control and Favorite conditions. As a result, the electromyogram of the ulnar flexor muscle of the wrist in the dominant hand, which is a performance index, showed significant differences between the two conditions. The R-R Interval, which is the physiological index, showed no significant differences between the two conditions. Additionally, the impression of the feelings, which is the psychological index in the Favorite condition were higher than those in the Control condition. Therefore, it is suggested that there is a psychological change as a primary effect of listening to favorite music during daily life behavior, and the performance may be improved as a secondary effect of the psychological change. In conclusion, listening to favorite music decreased the mental fatigue, which is associated with the subjective feelings.