impact. When these differences were large, the detector determined a fall had occurred.
Srinivasan et al. [6] described a wireless fall detector consisting of a triaxial accelerometer and passive infrared motion detectors. Users wore the accelerometer on their wrist. The motion detectors were embedded in the envi- ronment. That system detected falls based on the mea- sure of normalized energy expended from the accelera- tion value sensed by the accelerometer. Falls were con- firmed based on the subsequent absence of motion, which was observed by the infrared motion detectors.
Some problems remained in the systems developed by these researchers. First, they could not determine what had triggered falls by the elderly. Second, they could not detect abnormal conditions other than falls as abnor- mal heart rates. Third, these systems could only be used in limited areas because the sensors used in them were embedded in the environment and several sensors were used. As a result the users could not walk with them. Fourth, these systems were not frequently used due to reasons of appearance that encroached on human dignity. Finally, these systems did not work under normal con- ditions. Therefore, the systems were useless things for most of the time users wore them.
To resolve the first, second and third problems, we have already proposed the Abnormal Condition Detec- tion System (ACDS) using a wireless wearable biosensor [7]. To resolve the fourth and fifth problems, the systems should be more user-friendly and provide useful features that encourage use of the system even under normal con- ditions. We have currently focused our attention on the health problems that many elderly people are experienc- ing. The lack of exercise is the most serious problem for the elderly. Taking these facts into consideration, we propose the implementation of a feature that displays the degree of exercise.
impact. When these differences were large, the detector determined a fall had occurred.
Srinivasan et al. [6] described a wireless fall detector consisting of a triaxial accelerometer and passive infrared motion detectors. Users wore the accelerometer on their wrist. The motion detectors were embedded in the envi- ronment. That system detected falls based on the mea- sure of normalized energy expended from the accelera- tion value sensed by the accelerometer. Falls were con- firmed based on the subsequent absence of motion, which was observed by the infrared motion detectors.
Some problems remained in the systems developed by these researchers. First, they could not determine what had triggered falls by the elderly. Second, they could not detect abnormal conditions other than falls as abnor- mal heart rates. Third, these systems could only be used in limited areas because the sensors used in them were embedded in the environment and several sensors were used. As a result the users could not walk with them. Fourth, these systems were not frequently used due to reasons of appearance that encroached on human dignity. Finally, these systems did not work under normal con- ditions. Therefore, the systems were useless things for most of the time users wore them.
To resolve the first, second and third problems, we have already proposed the Abnormal Condition Detec- tion System (ACDS) using a wireless wearable biosensor [7]. To resolve the fourth and fifth problems, the systems should be more user-friendly and provide useful features that encourage use of the system even under normal con- ditions. We have currently focused our attention on the health problems that many elderly people are experienc- ing. The lack of exercise is the most serious problem for the elderly. Taking these facts into consideration, we propose the implementation of a feature that displays the degree of exercise.
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