Takenao Sugi

Clinical application of automatic integrative interpretation of awake background EEG: quantitative interpretation, report making, and detection of artifacts and reduced vigilance level

Methods for the automatic detection of artifacts and vigilance level of the EEG record were developed for a preprocessing procedure for the automatic integrative interpretation of awake background EEG. All equations for the detection were derived such that they would conform to the procedure that an EEGer adopts for visual EEG inspection. The automatic EEG interpretation system was improved by adding the proposed preprocessing procedure and gave satisfactory interpretation results for the EEG data even contaminated with artifacts or in the drowsy state. The automatic EEG interpretation method proposed here is suggested for clinical use as an assistant tool for EEGers and physicians.

An Automatic Spike Detection System Based on Elimination of False Positives Using the Large-Area Context in the Scalp EEG

Most automatic spike detection systems in the scalp electroencephalogram (EEG) focused on the characteristics of “spike.” However, the characteristics of “false positives” (FPs) have not been fully studied. In this paper, we proposed a system that contains a series of algorithms to eliminate FPs and a template method to confirm spikes. The system used large area context available on 49 channels from two common montages. The impact of slow-waves after spikes was taken into consideration, as well as the information from single channel, multichannel, and whole recording. Two types of FPs were identified in this paper. The ones from typical artifacts were identified by analysis of background EEG activities, and the ones from other EEG activities were declared by spatial and temporal characteristics of spike activities. Finally, a multichannel template method was used to assess the performance of the proposed system. The system was evaluated using 17 routine EEG recordings. Spike activities were observed in six of them. Effective multichannel templates were extracted from four recordings containing frequent spikes. The least selectivity was 92.6% and the most false positive rate was 0.26 min-1. Proposed algorithms for elimination of FPs are also suitable for other algorithms to enhance performance since most FPs can be identified while few true spikes are eliminated.

Automatic EEG arousal detection for sleep apnea syndrome

Abstract Electroencephalographic (EEG) arousals are seen in EEG recordings as an awakening response of the human brain. Sleep apnea is a serious sleep disorder. Severe sleep apnea brings about EEG arousals and sleep for patients with sleep apnea syndrome (SAS) is thus frequently interrupted. The number of respiratory-related arousals during the whole night on PSG recordings is directly related to the quality of sleep. Detecting EEG arousals in the PSG record is thus a significant task for clinical diagnosis in sleep medicine. In this paper, a method for automatic detection of EEG arousals in SAS patients was proposed. To effectively detect respiratory-related arousals, threshold values were determined according to pathological events as sleep apnea and electromyogram (EMG). If resumption of ventilation (end of the apnea interval) was detected, much lower thresholds were adopted for detecting EEG arousals, including relatively doubtful arousals. Conversely, threshold was maintained high when pathological events were undetected. The proposed method was applied to polysomnographic (PSG) records of eight patients with SAS and accuracy of EEG arousal detection was verified by comparative visual inspection. Effectiveness of the proposed method in clinical diagnosis was also investigated.

A methodology for designing controllers for industrial systems based on nonlinear separation model and control

Abstract A feasible method of controller design for industrial nonlinear dynamic systems is proposed, by separating the nonlinear dynamic system into nonlinear static parts and a linear dynamic part. The proposed method of industrial controller design reduces the existing gaps between the control theory and the actual field. In the controller construction procedure of a system, the nonlinearities are eliminated by using the inversion functions of the nonlinear static parts. Any conventional control theory is ideally applicable to a linear dynamic part of the system. Based on the proposed method of nonlinear separation, controllers were constructed for three different systems: a chemical reactor, a temperature level-controlled tanked water system, and the contour-following control of an articulated robot arm. Some encouraging control performances, superior to those of other existing controllers, showed its significant potential for application to industrial systems with nonlinearities.

Development of meal assistance orthosis for disabled persons using EOG signal and dish image

A meal assistance orthosis is developed for elderly and/or disabled persons who have partly or completely lost the ability of moving their upper limbs by themselves independently. The meal assistance orthosis supports the disabled persons and brings foods from dishes to their mouth by their own forearms. Target positions of the meal assistance orthosis, i.e., the scooping points on dishes can be determined by using image processing of the dish image taken by a video camera. Human intention of food selection can be extracted from electrooculogram (EOG) signals which are measured by electrodes on the face. Position control is adopted for control strategy of the meal assistance orthosis and force-free control which can realise flexible motion of the meal assistance orthosis is adopted in order to avoid injuring the users. The effectiveness of the developed meal assistance orthosis is assured by experimental works on normal persons.

Experimental evaluation of teleoperation system with force-free control and visual servo control by human operator perception

This research considers the teleoperation of an articulated robot arm by means of force-free control and visual servo control (VSC) over communication channels using the Internet technology. A semi-autonomous type teleoperation system contains a human supervisory control and VSC schemes and switches one scheme to another for accomplishing the required task accurately. The main investigation is carried out to find how it effectively improves the accuracy and the effectiveness of the teleoperation after provision of a visual feedback channel to the system. The system accuracy, effectiveness, repeatability and handleability based on the human operator’s skills and operator’s cognitive aspects are evaluated using experimental results and statistical data analysis. Effectiveness of the statistical analysis is assured by increasing the number of experiment data and assuming environmental factors, and implicit variables maintain to be unchanged. Correlation coefficients are calculated to find out how controlled input parameters are related to the successful output given by the system.

Real-time control strategy for EMG-drive meal assistance robot — my spoon

The paper presents an ongoing investigation of applying finite state machines (FSM) to drive a meal assistance robot based on electromyogram (EMG) signals. An adapting single-threshold method on EMG power is proposed to recognize different elevation gestures. Predefined control commands are output by FSM based on the extracted EMG features, and used to operate the robot. The performance of control mode is tested in efficiency and comfortableness by both subjective and objective indices. And the high performance of the EMG-control meal assistance robot makes it feasible for users with upper limbs motor disabilities.

Human Intention Extracted from Electromyography Signals for Tracking Motion of Meal Assistance Robot

The objective of the present study is to determine if surface electromyography (EMG) signals can be used for controlling the motion of the meal assistance robot. The power of four EMG channels were calculated and encoded into five commands to track the motion of meal assistance robot. The results indicated that by using EMG signals, the meal assistance robot was able to follow the movement desire of the subjects and help them to eat. This study has shown the possibility of extracting the features of EMG signals that reflect the subjects intent as control signals.

Modeling of motor control on manual tracking for developing a handmovement-compensation technique

Skillful motor control by humans is achieved by the appropriate motor commands generating from the central nervous system. An internal model in the cerebellum may contribute to the realization of accurate motor control. In this work, a model of human motor control of manual tracking to move a visible target was constructed based on experimental data from a visual tracking test with normal healthy adults and with patients with cerebellar ataxia. A compensation method to improve the motor function of patients was also developed by using the model.

Artificial realization of human on-off decision making based on the conditional probability of a database

As human on-off decisions are the basic problems in our human lives, the analysis of human on-off decision making is an interesting topic. The procedures of qualified human decision making include many intuitive factors which have been acquired from previous valuable experience and gained through learning, but they may not be easily understood by others within a short period. By the use of a database of causes and decisions made by qualified experts for an objective event, human decision making for that event can be realizable artificially. This paper investigates a general method for realizing artificial human on-off decision making based on the conditional probability of the database. As on-off decision making is a discrete event and the causes for that decision making are continuous events, a mathematical treatment of a Dirac delta function in a probability density function is required to derive the conditional probability for the decision making. Several examples of artificial human decision making by the proposed method were demonstrated, and the results obtained showed good agreement with those of human experts in the respective fields.