Brain dysfunction evaluation system, brain dysfunction evaluation method, and program
A system for evaluating a degree of brain dysfunction of a subject, such as a decline in cognitive function, calculates a difference in movement functions between both hands in a coordination movement. The system includes a storage device for storing time-series data on a finger movement task of each of both hands of a test subject acquired by a movement sensor; a data processing device for analyzing the time-series data stored in the storage device; and a display device for displaying an analysis result analyzed by the data processing device. The data processing device includes a movement waveform generation unit for generating a movement waveform corresponding to the time-series data stored in the storage device; and a difference-between-hands feature quantity generation unit for generating a difference-between-hands feature quantity which represents a difference in respective finger movement tasks between both hands, based on the respective movement waveforms of both hands.
1. A finger movement evaluation system, comprising:
one or more movement sensors configured detect finger-to-thumb tapping with both hands opening and closing simultaneously of a test subject;
a memory configured to store therein time-series data on the finger-to-thumb tapping acquired by the movement sensor;
a data processor configured to analyze the time-series data stored in the memory; and
a display configured to display an analysis result analyzed by the data processor,
wherein the data processor configured to:
based on the time-series data stored in the memory, generate a movement waveform of each of both hands of the test subject, each corresponding to the time-series data;
based on the generated movement waveform of each of both hands of the test subject, generate a difference-in-both-hands waveform which is a difference between the respective movement waveforms of both hands, the difference-in-both-hands waveform containing a first frequency which is a frequency of the finger-to-thumb tapping and a second frequency which is a frequency as a variation cycle for eliminating displacement between both hands; and
based on the generated difference-in-both-hands waveform, generate a difference-between-hands feature quantity.
2. The finger movement evaluation system according to claim 1 ,
wherein the data processor is configured to:
calculate a frequency spectrum by applying Fourier transform to the difference-in-both-hands waveform; and
determine, as the difference-between-hands feature quantity, a smaller frequency selected from respective frequencies corresponding to each of two strongest peak values of the calculated frequency spectrum.
3. A finger movement evaluation system, comprising:
a terminal device that comprises one or more movement sensors configured to detect finger-to-thumb tapping with both hands opening and closing simultaneously of a test subject, and a first communication device; and
a server that comprises a second communication device configured to communicate with the terminal device, a memory configured to store therein time-series data on the finger-to-thumb tapping, which is acquired from the movement sensor via the second communication device, a data processor configured to analyze the time-series data stored in the memory, and a display configured to display an analysis result analyzed by the data processor,
wherein the data processor of the server is further configured to:
based on the time-series data stored in the memory, generate a movement waveform of each of both hands of the test subject, each corresponding to the time-series data;
based on the generated movement waveform of each of both hands of the test subject, generate a difference-in-both-hands waveform which is a difference between the respective movement waveforms of both hands, the difference-in-both-hands waveform containing a first frequency which is a frequency of the finger-to-thumb tapping and a second frequency which is a frequency as a variation cycle for eliminating displacement between both hands; and
based on the generated difference-in-both-hands waveform, generate a difference-between-hands feature quantity.
4. A finger movement evaluation method using a finger movement evaluation system that comprises: one or more movement sensors configured to detect finger-to-thumb tapping with both hands opening and closing simultaneously of a test subject; a memory configured to store therein time-series data on the finger-to-thumb tapping, which is acquired by the movement sensor; a data processor configured to analyze the time-series data stored in the memory; and a display configured to display an analysis result analyzed by the data processor, the finger movement evaluation method comprising:
a step of generating, by the data processor, based on the time-series data stored in the memory, a movement waveform of each of both hands of the test subject, each corresponding to the time-series data;
a step of generating, by the data processor, based on the generated movement waveform of each of both hands of the test subject, a feature quantity of each of both hands;
a step of generating, by the data processor, based on the generated movement waveform of each of both hands of the test subject, a difference-in-both-hands waveform which is a difference between the respective movement waveforms of both hands, the difference-in-both-hands waveform containing a first frequency which is a frequency of the finger-to-thumb tapping and a second frequency which is a frequency as a variation cycle for eliminating displacement between both hands; and
a step of generating a difference-between-hands feature quantity, by the data processor, based on the generated difference-in-both-hands waveform.
5. The finger movement evaluation method according to claim 4 ,
wherein, under control of the data processor,
a frequency spectrum is calculated by applying Fourier transform to the difference-in-both-hands waveform, and
a smaller frequency selected from respective frequencies corresponding to each of two strongest peak values of the calculated frequency spectrum is determined as the difference-between-hands feature quantity.