Development of simple motion analysis device and software

OData support
Dr. Pataki Béla
Department of Measurement and Information Systems

In developed countries with the increasing rate and number of elderly people the examination and monitoring of the condition of movement disorder with simple instruments – perhaps at home if you like – have become more important. Home accidents, of which a large number are due to locomotor disorder, are very often the reason of deteriorating living standards, or many times are even the cause of death. These types of accidents can be avoided with high probability if we can detect the early stage of locomotor disorders. Monitoring can be achieved by the measurement of simple parameters (force, pressure, acceleration) with an instrument placed on the body or in the home of the patient.

The aim of the work is designing an instrument for monitoring the condition of movement disorder and the implementation and testing the controller and signal processing software. This thesis presents the requirements made by the specialities of the topic (low power, fitting into home environment, low price, etc.) and the compromise-made solutions considering them.

During the implementation a load sensor based surface („sensor-rug”) was developed, which is thin, but still has a large area and by which we are able to monitor the patient at home, to define his or her motion status and detect a possible fall. During the design we have found the most suitable measuring principle, which makes possible to measure the amount of load on each sensor in the simplest and cheapest way. After the multi-step prototype development the final hardware was formed which is large enough to cover a whole room placing the modules next to each other. Both the embedded operating software and the PC-side data acquisition and signal processing software were written. Using these, we were able to achieve the target task of making distinction among different types of motions. And we were also able to detect the event of a possible fall.


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