1.Our system monitors the care-receiver through sensors installed indoors and sends an alarm to mobile phones of his/her caregivers upon detection of the following accidents:
・A fall in the living room or other indoor spaces
・A fall in the bathroom or drowning in the bathtub
・No signs of using the toilet, refrigerator, etc. and no detection by the motion sensors although the person is home
・A fall off the bed, seizure on the bed, and bed-leaving by those with low mobility
2.Our system e-mails the care-receiver’s activity record collected through sensors to let caregivers know about his/her safety and daily living pattern.
3.Our system is so easy to use and virtually maintenance free that the care-receiver is hardly aware of having it in his/her living spaces.
4.We offer the system at a reasonable price to keep extra load on the household budget as low as possible.
5.The daily living pattern provided through our system can be analyzed and used to improve the pattern and make practical plans for nursing care and home visits.
1.Our monitoring system uses Doppler sensors and a unique algorithm to measure the location, body position and activity of the care-receiver and detect a fall or drowning.
2.Our monitoring system uses motion and pressure sensors with a unique algorithm to detect bed-leaving, body movements, seizures, etc. based on the care-receiver’s motions and weight distribution on the bed.
3.Our monitoring system collects information from sensors installed in various spaces of the house and wirelessly sends to the cloud computing system for information management and analysis.
The name of the robot care equipment | Monitoring aid system for nursing care at private homes |
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Company name | AVIS Corporation |
Target area | Monitoring system for dementia patients |
Expected target user | Elderly people living at home, their families, nursing care providers, etc. |
Assumed environment |
Place: Indoor spaces (living rooms, bathrooms, bedrooms, etc.) in private homes Time: 24 hours |
Sales date | April 2015 (April 2018 for optional fall detection) |