We measured the electrical activity signals of the heart through vital signs monitoring garments that have textile electrodes in conductive yarns while the subject is in stable and dynamic motion conditions. To measure the electrical activity signals of the heart during daily activities, four types of monitoring garment were proposed. Two experiments were carried out as follows: the first experiment sought to discover which garment led to the least displacement of the textile electrode from its originally intended location on the wearer's body. In the second, we measured and compared the electrical activity signals of the heart between the wearer's stable and dynamic motion states. The results indicated that the most appropriate type of garment sensing-wise was the "cross-type", and it seems to stabilize the electrode's position more effectively. The value of SNR of ECG signals for the "cross-type" garment is the highest. Compared to the "chest-belt-type" garment, which has already been marketed commercially, the "cross-type" garment was more efficient and suitable for heart activity monitoring.
A small and wireless accelerometer system was developed for the estimation of temporal gait parameters. The new system was built using two 3-axis accelerometers. Measurement's accuracy was assessed using as a criterion standard provided by foot switches. To assess the consistency of this system, estimates of heel contact and toe off time based on accelerometers and those based on footswitches were compared for 20 steps from 8 individual healthy subjects. Accelerometers and footswitches had high consistency in the temporal gait parameters. The stance, swing, single support, and double support time of gait cycle revealed ICCs values of 0.95, 0.93, 0.86, and 0.75 on the right and 0.96, 0.86, 0.93, 0.84 on the left, respectively. Therefore, this system proved to be a reliable tool for identification of temporal gait parameters.
The concept of intelligent toothbrush, capable of monitoring brushing motion, orientation through the grip axis, during toothbrushing was suggested in our previous study. In this study, we describe a tooth brushing pattern classification algorithm using three-axis accelerometer and three-axis magnetic sensor. We have found that inappropriate tooth brushing pattern showed specific moving patterns. In order to trace the position and orientation of toothbrush in a mouth, we need to know absolute coordinate information of toothbrush. By applying tilt-compensated azimuth (heading) calculation algorithm, which is generally used in small telematics devices, we could find the inclination and orientation information of toothbrush. To assess the feasibility of the proposed algorithm, 8 brushing patterns were preformed by 6 individual healthy subjects. The proposed algorithm showed the detection ratio of 98%. This study showed that the proposed monitoring system was conceived to aid dental care personnel in patient education and instruction in oral hygiene regarding brushing style.
The design of an intelligent toothbrush, capable of monitoring brushing motion, orientation through the grip axis, during toothbrushing is described. Inappropriate tooth-brushing styles, even in adults, sometimes cause dental problems, cavities, gingivitis, etc. This smart system provides user to monitor his or her brushing pattern using accelerometer and magnetic sensors for evaluation of toothbrushing style. Directional information of toothbrush with respect to the earth's magnetic field and activity data were measured by a miniaturized low-power micro-controller, MSP430 and transmitted to personal computer by 2.4 GHz radio transmitter, nRF2401. A personal computer provides an on-line display of activity and orientation measurements during toothbrushing. The signal trace is then analyzed to extract clinically relevant information. This preliminary study showed that the proposed monitoring system was conceived to aid dental care personnel in patient education and instruction in oral hygiene regarding brushing style.
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