Abstract
This paper proposes a stair walking detection via Long-short Term Memory (LSTM) network to prevent stair fall event happen by alerting caregiver for assistance as soon as possible. The tri-axial accelerometer and gyroscope data of five activities of daily living (ADLs) including stair walking is collected from 20 subjects with wearable inertial sensors on the left heel, right heel, chest, left wrist and right wrist. Several parameters which are window size, sensor deployment, number of hidden cell unit and LSTM architecture were varied in finding an optimized LSTM model for stair walking detection. As the result, the best model in detecting stair walking event that achieve 95.6% testing accuracy is double layered LSTM with 250 hidden cell units that is fed with data from all sensor locations with window size of 2 seconds. The result also shows that with similar detection model but fed with single sensor data, the model can achieve very good performance which is above 83.2%. It should be possible, therefore, to integrate the proposed detection model for fall prevention especially among patients or elderly in helping to alert the caregiver when stair walking event occur.
Highlights
Among so many indoor activities of daily living (ADL), stair walk is the one that have a major potential and hazardous for people to falls especially elderly
Varying input sensor data In the third stage, the sensor input data used is varied while fixing the window size at 2 seconds a nd Long Short-Term Memory (LSTM) network a rchitecture a t double la yered with 250 hidden cell units per la yer
Deep structured LSTM network models was implemented to detecting stair walking event as well a s other activities of daily activities
Summary
Among so many indoor activities of daily living (ADL), stair walk is the one that have a major potential and hazardous for people to falls especially elderly It might cause significant injuries such as hip fracture, traumatic brain injuries (TBI) and deaths. An environment-related factor is the factors that cause by environment of host which include stair architecture design, and stair obstacles such as absence of handrail, irregular riser height and object left on stairs. These factors will force the staircase user to use their m aximal ca pa bilities to wa lk up or down the sta irs a s grea ter body posture control effort is required. This can reduce the burden of caregiver by alerting caregiver as soon as any stair wa lk a ctivity is detected before a ny sta ir fa ll ha ppen
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