Recently, a contactless method for measuring a biological signal using a video camera has garnered attention. Especially, video plethysmography, a technique for obtaining a pulse wave from a video, is useful for managing the health of people on a daily basis. However, any body movement of a person subjected to the measurement leads to the generation of irregular noise in video plethysmography and reduces the accuracy of the recorded biological information, e.g., heart rate, during the measurement. Blind source separation is a popular technique for eliminating noise from the results of video plethysmography comprising different multiple-color channels. However, it is difficult to apply this technique to a single-color video such as a near-infrared video. Herein, a new method that combines singular spectrum analysis with the circular autocorrelation function is introduced to eliminate irregular noise in single-color video plethysmography. Applying the proposed method on videos collected from 39 individuals improved the estimation accuracy of instantaneous heart rate by approximately 44% over a conventional method using a linear filter. Furthermore, the proposed method also enabled more precise estimations of the heart rate than that achieved using multi-color video plethysmography.

A cycling wheel chair (CWC) is a pedal-driven wheelchair developed as a personal transportation device for patients with hemiplegia after cerebral stroke. The CWC enables the patient to travel much faster than an ordinary wheel chair and is effective for prevention of disuse syndrome in lower limbs. However, the patients often have impairment of cognitive function as well as motor function. It is dangerous for such patients to ride on the CWC on outdoor roads. To cope with this problem, a virtual reality system for the CWC named “Virtual CWC” was developed. The Virtual CWC can provide safe and space-saving training and test environment for the patients. In the present study, a new scenario of the Virtual CWC has been developed to test the patient's cognitive function with respect to navigation as well as driving skills. The normal subjects' “homing vectors” obtained after riding on the Virtual CWC in three kinds of routes were analyzed, and compared between a young group (26 normal subjects; age 23.9 ± 2.5) and an elderly group (14 normal subjects; age 69.9 ± 4.1). As a result, the effect of cooperation between pedaling and steering could be found in the angular error of homing vectors in the case of the elderly group.