Breath to speech communication with fall detection for elder/patient with take care analytics

People suffering from Developmental-Disabilities are almost entirely paralyzed disabling them to communicate in any way except using an Augmentative and Alternative Communication device. Survey analysis tells that 1.4% of globe's population suffers from speech disorder which is more than the Karnataka's population. Looking into the elderly group it was analyzed that the fall events cannot be predicted and might be an unsafe event. Estimates tell that 33.33% of 65 and above aged people fall every year. It can be seen that out of these falls 55% occur at home and 23% occur near the home. Hence, a dependable fall detection system has to be developed, and commercially be used all over the globe among the elderly. Depending on fast detection and delivering signals, the cost of the system can be reduced which is interconnected to the reaction and saving time. An enhanced breathe to speech communication and fall detection system for elderly people and also monitoring through a take care analytics is suggested that are based on intelligent sensors that are put by the person using that device.