Return to daily life Early mobilization program Comprehensive CR (disease management program) Discharge from hospital, Return to home Maintain comfortable life, Prevention of recurrence Returning to society-workforce, Establish new healthy lifestyle Inpatient rehabilitation program (CCU/ICU/ward) *Notation of corporation is omitted.
The purpose of our study was to determine the electrooculography (EOG) interface that can be used for amyotrophic lateral sclerosis (ALS) patients that can use without preparation. We proposed eye movement detection using Root Mean Square the active threshold (AT method) and k-nearest neighbor (k-NN) methods. The AT method is the threshold method that is dynamically calculated using the root mean square. This report describes the combined use of both methods. We conducted experiments on the waveform detection accuracy for 19 healthy subjects between the ages of 20 and 29 years. The hit rate for the proposed method was 94%, and the FA rate was 9%. Next, we calculated the information transfer rate (ITR), a popular evaluation index in for the brain-computer interface. (BCI). The minimum ITR using the proposed method was 19.02[bits/min]. The ITR of the P300 speller a BCI tool, was 16.4[bits/min]. The ITR of the proposed method was higher than that using the P300 speller. Therefore, it can be said that the proposed method has usefulness as an interface.
Switch using bio-signal are researching for communication of a physically disabled person such as ALS. We have researched bio-signal device for daily life support of ALS patients using ocular potential. We suggested Doubled Constant to RMS (DCR) method that is dynamic calculate the threshold value using RMS to detect to intentional action. However, DCR method has problem that the threshold increase from signal fluctuation, and cannot be detected large electrooculography change by intentional action. We need research better method for detection to intentional action. In recent years, it has been found that classification by pattern recognition in intentional action gives high accuracy for EMG. We compared the DCR method and the k neighborhood method which is one of the pattern recognition. It is because, Bio-signal switch has need better detection method. In result, each method has different detect conditions. In future, DCR method and knn method are combined for improved accuracy, and consider online analysis on EOG.
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