Jeffry Bonar Fernando

Improvement of human identification accuracy by wavelet of peak-aligned ECG

In this paper, a novel method of human identification using electrocardiogram (ECG) is proposed. In the method, while normalizing RR interval, in addition to normalized signal where time interval of P wave, Q wave, R wave, S wave relatively to R wave is unaligned, normalized signal where time interval of those peaks is aligned is also generated. Wavelet transform is then applied to both normalized signals and feature vector is extracted from their wavelet coefficients. ECG data are collected from 10 subjects using a pair of dry electrodes which are held by two fingers. Experiment results show that adding wavelet of peak-aligned ECG improves the classification accuracy, where the maximum accuracy is 100%, 97%, and 90% for data measured in more than 20 seconds, 5 seconds, and 3 seconds respectively.

Estimation of respiratory signal from thoracic impedance cardiography in low electrical current

A new method to estimate respiratory signal from thoracic impedance is proposed. To realize battery powered, wearable respiratory monitoring devices, low current impedance measurement techniques are desired. However, under low current conditions, conventional methods to separate cardiac and respiratory signals do not work well as the cardiac signal is much larger than the respiratory signal. In the proposed method, respiratory signal is estimated by calculating an envelope curve from the detected T waves of cardiac component. The results of the experiments show that the accuracy of proposed method is greater than conventional method.

Collision avoidance path planning for hospital robot with consideration of disabled person's movement characteristic

A novel algorithm of collision avoidance path planning, especially for hospital robot, is proposed. The algorithm puts into consideration the movement characteristic of various kinds of disabled person, which are represented by wheelchair user and crutch user here. A model which implies the energy to move to a certain point from present location is introduced for each kind of disabled person. The model does not only consist of the distance to target point, but also the rotation angle and the persons easiness to change direction. Based on what kind of person the oncoming person is, the robot uses the appropriate model and estimates the easiest path for the person to move. Then, the robot plans an avoidance path.

A multi-holding-pose enrollment method for robust ECG identification

In this paper, a new enrollment method for human identification using ECG is proposed. In the method, ECG data of a user are enrolled from five different poses while the user is holding a pair of dry electrodes from an ECG sensor with both hands. The five poses are when the user is holding the sensor in the center, left side, right side, upside, and downside of the users body. The ECG data are collected from nine subjects and classification is performed by three existing algorithms and an original algorithm. Experiment results show that identification accuracy when ECG data are enrolled by the proposed method is improved from 3 to 13 percentage points than when they are enrolled in conventional single holding pose.

Estimation of muscle fatigue by ratio of mean frequency to average rectified value from surface electromyography

A new method to estimate muscle fatigue quantitatively from surface electromyography (EMG) is proposed. The ratio of mean frequency (MNF) to average rectified value (ARV) is used as the index of muscle fatigue, and muscle fatigue is detected when MNF/ARV falls below a pre-determined or pre-calculated baseline. MNF/ARV gives larger distinction between fatigued muscle and non-fatigued muscle. Experiment results show the effectiveness of our method in estimating muscle fatigue more correctly compared to conventional methods. An early evaluation based on the initial value of MNF/ARV and the subjective time when the subjects start feeling the fatigue also indicates the possibility of calculating baseline from the initial value of MNF/ARV.