JP2005152053A - Action analyzing apparatus and utilization of the same - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus which can quantitatively analyze and evaluate cardinal symptoms of a disease followed by dyskinesia such as Parkinsonism or the like for a diagnosis, severeness degree judgment, the effect of a medicine evaluation and effect judgment of surgical treatment or the like of the disease followed by dyskinesia such as Parkinsonism or the like, and the utilization of the same. <P>SOLUTION: The action analyzing apparatus 1 for an analysis of the finger action of an examinee is equipped with two or more acceleration sensors 2 and 2 which are removably attached to two or more fingers of the examinee, and an analyzing apparatus which performs a prescribed arithmetic processing of an output signal from the acceleration sensors 2 and 2 and analyzes at least one of rhythm disorder, amplitude and reaction force of the action of the fingers fitted with the acceleration sensors 2 and 2. The symptoms of the disease followed by dyskinesia can be quantitatively analyzed by the action analyzing apparatus 1. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an apparatus for analyzing the movement of an animal such as a human and the use thereof, and more specifically, using an acceleration sensor, for example, a major in diseases associated with movement disorders such as Parkinson's disease. The present invention relates to a motion analysis apparatus for analyzing symptoms and use thereof.

  Parkinson's disease is a neurological disease accompanied by movement disorders caused by a lack of dopamine in the striatum of the brain where nerve endings exist, and the number of patients is approximately 120,000 in Japan (rate of 1 per 1000 population) It is a disease that develops at a rate of 1 to 2 in every 1000 people in the world. The number of Parkinson's disease patients is high among middle-aged and elderly people after the age of 50. In Japan, where society is aging, the number is increasing year by year.

  The main cause of the onset of Parkinson's disease is said to be basal ganglia disorder. That is, dopamine, a neurotransmitter, is generated and projected on the striatum in normal midbrain nigra neurons, but in Parkinson's disease, degeneration / dropout occurs in these midbrain neurons. Insufficient dopamine is thought to cause abnormalities in the function of the basal ganglia, resulting in movement disorders (extrapyramidal symptoms). However, because the detailed cause is unknown and it is difficult to cure, Japan has been designated as an intractable disease by the Ministry of Health, Labor and Welfare.

  The four main symptoms of Parkinson's disease are known as “tremor”, “muscle rigidity”, “slow movement (peristalsis) / immobility”, and “postural reflex disorder”. “Treasure” is a symptom in which hands and feet swing freely when not moving. “Muscle strength” is a symptom in which the joint does not move smoothly, such as when the muscles become tense and stiff and the movement of the limbs slows, or when another person moves the limbs, resistance is felt. A typical example is a gear-like muscle stiffening that moves smoothly without the joints moving smoothly. “Slow motion (peristalsis) / no motion” is a symptom in which walking is slowed down, the stride is reduced, and movement is slowed down. “Posture reflex disorder” is a symptom in which the body becomes unbalanced and easily falls, and when the posture is pushed before tilting, it becomes difficult to reestablish the posture and the body falls forward.

  In addition, as a characteristic of Parkinson's disease, there is no characteristic in imaging findings such as blood test and MRI (magnetic resonance imaging) head image test, and it is not a reference for judgment of onset and severity. For this reason, Parkinson's disease is diagnosed with reference to the above-mentioned main symptoms (clinical symptoms) of Parkinson's disease and patient complaints.

  For example, as a conventionally known diagnostic device for diagnosing Parkinson's disease, a so-called finger that strikes a keyboard with one finger and tries to diagnose major symptoms of Parkinson's disease from the interval and speed of the tapping operation Many tapping (finger tap) diagnostic devices and diagnostic methods have been reported (for example, see Non-Patent Documents 1 to 4).

On the other hand, a motion analysis device, a life activity monitoring device, a portable accident monitoring device, a walking observation method and an observation device for elderly people, which are equipped with an acceleration sensor etc. on the body and process the output value to analyze the motion Also known are body motion sensing devices that support rehabilitation of Parkinson's disease patients (see, for example, Patent Documents 1 to 6).
JP 2000-157516 A (publication date: June 13, 2000) JP-A-6-285046 (Publication date: October 11, 1994) JP-A-8-335460 (Publication date: December 16, 1996) JP 10-295649 A (publication date: November 10, 1998) JP 2001-198110 A (publication date: July 24, 2001) JP 2002-78697 A (publication date: March 19, 2002) Carl Nikolaus Homann, et al., Movement Disorders, Vol.15, No.4, 2000, pp641-647 Helen M. Bronte-Stewart, et al., Movement Disorders, Vol.15, No.1, 2000, pp36-47 Jurgen Konczak, et al., Movement Disorders, Vol.12, No.5, 1997, pp665-676 Shimoyama, et al., Arch Neurol, Vol.47, June, 1990, pp36-47

  As described above, the finger tapping test is a widely used technique because it can easily evaluate Parkinson's disease coordination disorder, peristalsis, and immobility in a short time.

  However, diagnosis based on various clinical symptoms such as finger tapping often depends on the experience and ability of the doctor, and due to the subjective qualitative evaluation of the doctor, there are differences between the evaluators and within the evaluators. There is a problem that it occurs.

  Furthermore, the various devices using the above-described acceleration sensor and the like have many problems such as a large device, a high price, and a difficulty in wearability. Furthermore, when a finger tapping test is performed using a computer keyboard, mouse, pressure sensor, or MIDI (Musical Instrument Digital Interface) -compatible keyboard, only rhythm irregularities can be analyzed. There is a problem that even the evaluation of rhythm irregularities is an ambiguous analysis.

  As described above, many measuring devices and measuring methods for the main symptoms of Parkinson's disease have been reported, but none have been put into practical use and used for diagnosis as a testing device that can be used in clinical practice. The same applies to diseases associated with other movement disorders.

  Therefore, a device capable of quantitatively measuring and evaluating the main symptoms of the disease for diagnosis, severity determination, drug efficacy evaluation, and surgical treatment effect determination of diseases with movement disorders such as Parkinson's disease. Development is strongly desired.

  The present invention has been made in view of the above problems, and its purpose is for diagnosis, severity determination, efficacy evaluation, and surgical treatment effect determination of diseases associated with movement disorders such as Parkinson's disease. Another object of the present invention is to provide an apparatus capable of quantitatively analyzing and evaluating main symptoms of diseases associated with movement disorders such as Parkinson's disease and use thereof.

  As a result of intensive studies in view of the above-mentioned problems, the present inventors attach an acceleration sensor or the like to a predetermined part of the body, and apply a processing algorithm that incorporates the knowledge and experience of a neurologist to the output signal of the sensor. As a result, we developed an original device for obtaining medical data and evaluated the symptoms of patients with Parkinson's disease using this device, and found that the main symptoms of Parkinson's disease could be quantitatively evaluated, leading to the completion of the present invention. It was.

  That is, the motion analysis device according to the present invention is a motion analysis device for analyzing the motion of the finger of the subject's hand in order to solve the above-described problem, and is detachably attached to each of the plurality of fingers of the subject. A predetermined calculation process is performed on a plurality of acceleration sensors and a signal output from the acceleration sensor, and at least one of rhythm irregularities, amplitudes, and reaction forces in the movement of a finger on which the acceleration sensor is mounted And an analyzing means for analyzing one.

  Further, the analysis means is mounted with an acceleration waveform generation means for generating an acceleration waveform based on a signal output from the acceleration sensor, and an acceleration sensor based on the acceleration waveform generated by the acceleration waveform generation means. Based on the contact time detection means for detecting the contact time between the finger and the finger and the contact time between the finger and the finger detected by the contact time detection means, the interval between the times when the finger contacts the finger is calculated. And an interval calculating means.

  Further, the analysis means is mounted with an acceleration waveform generation means for generating an acceleration waveform based on a signal output from the acceleration sensor, and an acceleration sensor based on the acceleration waveform generated by the acceleration waveform generation means. Based on the contact time detection means for detecting the contact time of the finger and the finger, the contact time of the finger detected by the contact time detection means, and the signal output from the acceleration sensor. It is preferable to include a reaction force calculation unit that calculates a reaction force of the operation.

  Further, the analysis means is mounted with an acceleration waveform generation means for generating an acceleration waveform based on a signal output from the acceleration sensor, and an acceleration sensor based on the acceleration waveform generated by the acceleration waveform generation means. Contact time detecting means for detecting the time at which the finger contacts the finger, position waveform creating means for creating a position waveform by integrating the acceleration waveform created by the acceleration waveform creating means twice, and the position Amplitude calculation means for calculating the amplitude of finger movement based on the position waveform created by the waveform creation means and the finger contact time detected by the contact time detection means. Is preferred.

  Further, the interval calculation means preferably calculates a standard deviation of the interval between the time when the finger contacts the finger based on the time when the finger contacts the finger detected by the contact time detection means. . It should be noted that this “standard deviation of the interval between the times when the fingers come into contact with each other” can be regarded as a characteristic amount of irregular rhythm.

  Further, the reaction force calculating means detects the time of contact between the finger and the finger based on the time of contact between the finger and the finger obtained from the contact time detecting means, and the contact between the finger and the finger is detected. It is preferable that the reaction force is calculated by analyzing the acceleration component during the time period.

  In addition, the reaction force calculation means performs a low-pass filter process on the signal output from the acceleration sensor during the time when the finger is in contact with the finger, so that the reaction force time elapses. It is preferable that the reaction force in the finger movement is calculated by estimating.

  The low-pass filter processing is preferably performed at a cutoff frequency in the range of several Hz to several tens of Hz.

  Further, the amplitude calculating means calculates a position of a point where the distance is the longest from a straight line connecting two adjacent points among points where the finger contacts the finger in the position waveform as the amplitude of the finger movement. It is preferable.

  Further, it is preferable that the contact time detecting means performs a high-pass filter process on the acceleration waveform and converts the acceleration waveform into an absolute value so as to detect a time when the finger contacts the finger.

  The analyzing means further includes a position waveform creating means for creating a position waveform by integrating the acceleration waveform created by the acceleration waveform creating means twice, and the contact time detecting means includes an acceleration waveform. When it is not possible to detect the time when the finger and the finger contact based on the waveform, it is preferable to detect the time when the finger and the finger contact based on the position waveform created by the position waveform creating means.

  In addition, when the contact time detection unit cannot detect the time when the finger contacts the finger based on the acceleration waveform, the finger and the finger contact based on the position waveform created by the position waveform creation unit. It is preferable to detect the time to do.

  Furthermore, the motion analysis device includes a touch sensor that is detachably attached to a finger to which the acceleration sensor is attached. The acceleration sensor is attached to the back side of a plurality of fingers, and the touch The sensor is preferably attached to the abdomen side of the distal end portion of the plurality of fingers to which the acceleration sensor is attached.

  Further, the analyzing means includes a contact time detecting means for detecting a time at which the finger and the finger contact based on a signal output from the touch sensor, and a finger and the finger detected by the contact time detecting means. It is preferable that the apparatus includes an interval calculation unit that calculates an interval between movements of the fingers in contact with each other based on the contact time.

  Further, the analyzing means includes a contact time detecting means for detecting a time at which the finger and the finger contact based on a signal output from the touch sensor, and a finger and the finger detected by the contact time detecting means. It is preferable that the apparatus includes a reaction force calculation unit that calculates a reaction force of finger movement based on a contact time and a signal output from the acceleration sensor.

  In addition, the analysis means includes a contact time detection means for detecting a time at which the finger contacts the finger based on a signal output from the touch sensor, and an acceleration waveform based on the signal output from the acceleration sensor. Acceleration waveform creation means for creating the position waveform creation means for creating a position waveform based on the acceleration waveform created by the acceleration waveform creation means, the position waveform created by the position waveform creation means and the contact time detection It is preferable to include amplitude calculation means for calculating the amplitude of finger movement based on the contact time between the finger detected by the means.

  The plurality of fingers of the subject's hand are preferably a thumb and an index finger.

  Moreover, it is preferable that the motion of the finger of the subject's hand is a finger tapping motion. In this case, it is preferable that the finger tapping operation at this time is as fast as possible and the amplitude operation of the finger is increased as much as possible.

  The acceleration sensor is a single acceleration sensor that detects accelerations on three axes orthogonal to each other, and the analysis means performs data based on each signal of the acceleration sensor output corresponding to each axis. Is preferably calculated.

  In addition, in order to solve the above problems, the determination method according to the present invention uses any of the motion analysis devices described above to develop a disease accompanied by movement disorder, severity of the disease, evaluation of drug efficacy, and surgical treatment. One of the effects is determined.

  The disease is preferably Parkinson's disease.

  In addition, the screening method according to the present invention is characterized by screening a substance having a therapeutic effect on a disease associated with movement disorder using any one of the motion analysis apparatuses described above, in order to solve the above-described problem. Yes.

  The disease is preferably Parkinson's disease.

  The analysis apparatus may be realized by a computer. In this case, a control program for causing the computer to realize the analysis apparatus by operating the computer as each of the above means and a computer-readable recording medium on which the control program is recorded also fall within the scope of the present invention.

  As described above, according to the motion analysis apparatus according to the present invention, for example, among the main symptoms of diseases associated with movement disorders such as Parkinson's disease, coordination movement disorder, tremor, peristalsis / immobility, rhythm formation disorder, etc. There is an effect that it is possible to evaluate quantitatively. That is, it is possible to quantify the neurological findings that doctors have conventionally made in the examination room subjectively and qualitatively, and it is possible to record changes over time. This leads to the evaluation of objective clinical symptoms that are indispensable for practicing Ubiquitous Medicine, which has recently attracted attention.

  In addition, according to the motion analysis apparatus of the present invention, it is possible to analyze a component corresponding to a reaction force when a finger comes into contact with a finger that could not be measured by a conventional finger tapping test apparatus. The ability to analyze the magnitude of this reaction force makes it possible to newly analyze evaluation items that indicate movement disorders of Parkinson's disease in addition to items such as coordination movement disorders and peristalsis / immobility that were analyzed by conventional finger tapping tests. It is very significant in clinical medicine.

  As a result, the relationship between the reaction force that has not been evaluated so far and the symptoms of Parkinson's disease becomes clear, and a new clinical endpoint may be proposed. Furthermore, it can be expected to lead to elucidation of higher-order functional control of force.

  Further, according to the motion analysis apparatus according to the present invention, since the acceleration sensor is used, a non-invasive device that greatly reduces the burden of stimulation and restraint on the subject (patient) associated with the experiment / diagnosis / measurement. There is an advantage of being. In addition, since the acceleration sensor itself is inexpensive, there is an advantage that it is excellent in cost performance, and there is an advantage that the device itself is simple and has good portability and mountability during measurement.

  Furthermore, based on this quantified data, it is possible to determine a symptom of a disease associated with movement disorder. For example, there is an effect that it is possible to perform severity determination, drug efficacy determination, or surgical treatment effect determination of Parkinson's disease. For example, it is possible to determine the medication and surgical treatment effect based on EBM (Evidenced Based Medicine).

  In addition, by using the motion analysis apparatus according to the present invention, a substance or a drug having a therapeutic effect can be efficiently (in vivo) effectively treated for a disease associated with movement disorder (for example, a neurological disease such as Parkinson's disease). The effect that it can search is produced.

  One embodiment of the present invention is described below with reference to FIGS. Needless to say, the present invention is not limited to this.

[1] Motion Analysis Device The motion analysis device according to the present invention is a motion analysis device for analyzing the motion of fingers of a subject's hand, and includes a plurality of detachably attached to each of the plurality of fingers of the subject. Predetermined arithmetic processing is performed on the acceleration sensor and the signal output from the acceleration sensor, and at least one of rhythm irregularity, amplitude, and reaction force in the movement of the finger with the acceleration sensor is analyzed. It is only necessary that the apparatus includes an analyzing unit, and other specific configurations are not particularly limited.

  For example, as shown in FIG. 1, the motion analysis apparatus 1 according to the present embodiment amplifies a signal output from the acceleration sensor 2 in addition to the acceleration sensor 2 and the analysis apparatus 3 functioning as the analysis means. The amplifier 4 and the power source 5 are provided. According to the motion analysis apparatus according to the present embodiment, finger tapping (finger tap) motion can be analyzed. This "finger tapping action" is an action that repeats the action of bringing the thumb (thumb) and the index finger (index finger) into contact with and releasing from the same hand of the subject (the opposing movement of the thumb and index finger). is there. The motion analysis device 1 only needs to include the acceleration sensors 2 and 2 and the analysis device 3, and the amplifier 4 and the power source 5 are not necessarily required.

  Hereinafter, the components of the motion analysis apparatus 1 will be described in order. In particular, an acceleration sensor and an analysis apparatus that are characteristic parts of the present invention will be described in detail.

[1-1] Acceleration sensor 2
Here, two or more acceleration sensors 2 are necessary to be attached to a plurality of fingers in the subject's hand. The acceleration sensor 2 may be a physical property sensor or an elastic sensor as long as it can detect acceleration. In particular, a triaxial acceleration sensor that can detect accelerations on three axes orthogonal to each other is preferable. As a result, valid data can be obtained with certainty. Examples of the triaxial acceleration sensor include MA3-20 Ab manufactured by MicroStone, but are not limited thereto. In the present embodiment, two triaxial acceleration sensors are used as the acceleration sensor 2.

  As shown in FIG. 2, the acceleration sensor 2 is detachably mounted on the thumb and the index finger of the subject's hand. Of the acceleration sensors 2 and 2, one of the acceleration sensors 2 includes a mounting portion 2a for mounting the thumb, and the other acceleration sensor 2 includes a mounting portion 2b for mounting the index finger. . The attachment part 2a for attaching the thumb and the attachment part 2b for attaching the index finger may be a common member. Moreover, the specific structure of the attachment part of the acceleration sensor 2 is not specifically limited, For example, as shown in FIG. 2, it can attach to a test subject's finger | toe using a band. The acceleration sensor 2 is attached to the back side of the first joint of the finger, that is, the back side of the hand (the side with the nail). As described above, since the acceleration sensor 2 is a three-axis acceleration sensor, as shown in FIG. 2, accelerations on the X axis, the Y axis, and the Z axis that are orthogonal to each other can be detected. The detection principle (one example) of the acceleration sensor 2 will be briefly described with reference to FIG.

  As shown in FIGS. 3A and 3B, the acceleration sensor 2 includes a piezoelectric ceramic 21, a support base 22, a metal plate 23, and a weight 24. The acceleration sensor 2 outputs acceleration applied by one piezoelectric ceramic 21 as acceleration components in three directions of the X, Y, and Z axes. For example, when acceleration in the Z direction is applied to the acceleration sensor 2, the piezoelectric ceramic 21 is deformed as shown in FIG. The stress Fz at this time is proportional to the acceleration, and a voltage corresponding to the stress Fz is generated in the piezoelectric ceramic 21. On the other hand, when acceleration in the X or Y direction is applied to the acceleration sensor 2, the piezoelectric ceramic 21 is deformed as shown in FIG. The stress Fx at this time is proportional to the acceleration, and a voltage corresponding to the stress Fx is generated in the piezoelectric ceramic 21. When the acceleration sensor 2 outputs an analog signal, for example, an A / D (analog / digital) converter may be provided between the amplifier 4 and the analysis device 3 in FIG.

[1-2] Analysis device 3
Further, the motion analysis apparatus 1 includes an analysis apparatus 3. The analysis device 3 functions as an analysis unit that performs predetermined arithmetic processing on the time-series signal output from the acceleration sensor 2 and analyzes the motion of the finger on which the acceleration sensor is mounted. Hereinafter, an example of the analysis apparatus 3 will be described in detail with reference to FIG.

  FIG. 4 is a functional block diagram illustrating a configuration example of the acceleration sensors 2 and 2, the analysis device 3, the output device 40, and the information storage device 41. For ease of understanding, the power supply 5 and the amplifier 4 which are not characteristic parts of the present invention are omitted. As shown in the figure, the analysis device 3 includes an acceleration waveform creation unit 31, a contact time detection unit 32, a position waveform creation unit 33, a reaction force calculation unit 34, an interval calculation unit 35, and an amplitude calculation unit 36. The acceleration sensors 2 and 2 are attached to the thumb and index finger of the subject's hand as described above.

  The acceleration waveform creation unit 31 functions as an acceleration waveform creation unit that creates an acceleration waveform based on signals output from the acceleration sensors 2 and 2. Here, the “acceleration waveform” is a graphic that represents acceleration over time, with acceleration on the vertical axis and time (seconds) on the horizontal axis. Since two three-axis acceleration sensors are used, respective acceleration waveforms are created based on the acceleration signals in the X-axis, Y-axis, and Z-axis directions of the two acceleration sensors. That is, it can be said that the analysis device 3 calculates data based on each signal of the acceleration sensors 2 and 2 output corresponding to each axis. The acceleration waveform creation unit 31 not only creates a waveform by connecting signals actually obtained from the acceleration sensor, but also performs predetermined calculation processing based only on the numerical value of the output signal of the acceleration sensor, for example. Is also possible. In this case, the acceleration waveform creation unit 31 creates a virtual waveform. That is, the present invention includes an acceleration waveform creation unit 31 that virtually creates a waveform without actually creating a waveform, and actually performs a predetermined calculation process based only on the output information of the acceleration sensor.

  The contact time detection unit 32 detects a time at which the thumb and the index finger are in contact with each other based on the acceleration waveform created by the acceleration waveform creation unit 31 (detects the moment of contact over time). It functions. That is, the contact time detection unit 32 can detect a time (hereinafter also referred to as a finger contact point) when the thumb and the finger are in contact in the finger tapping operation.

  An example of a procedure in which the contact time detection unit 32 detects the contact time will be described with reference to FIG. FIG. 7 is a flowchart illustrating a procedure in which the contact time detection unit 32 detects finger contact points. The procedure for detecting the finger contact point by the contact time detection unit 32 includes pattern I (I region surrounded by a broken line in FIG. 7) and pattern II (II region surrounded by a broken line in FIG. 7). I will be described.

  The finger contact point is analyzed using only the Z-axis component signal in the acceleration sensor 2 attached to the index finger. The acceleration at time i on the Z-axis of the acceleration sensor 2 attached to the index finger is

Speed,

Let the position be z (i). However, i = 1, 2,..., N, and N is the data length. Let the sampling frequency be Fs. Sampling period T is set to T = 1 / Fs. In this embodiment, T = 10 ⁻⁴ seconds and N = 6 · 10 ⁵ . The j-th finger contact point is P _j and the finger contact interval (interval) is D _j .

  First, the contact time detection unit 32 performs (High Pass Filter; high-pass filter) on the acceleration waveform created by the acceleration waveform creation unit 31 in step 1 shown in FIG. Apply a cut-off frequency of 100 Hz) to remove the low-frequency swing phase (parts other than finger contacts in the finger tapping operation).

  Next, in S2, the contact time detection unit 32 calculates the absolute value of acceleration as shown in the following mathematical formula (1).

  Next, in S3, the contact time detection unit 32 sets 1/2 to 1/5 of the maximum amplitude as a threshold value (however, the maximum amplitude is determined from the front and back information according to the absolute value of the maximum amplitude), and the finger. Detect contact points. More preferably, the maximum amplitude is set to 1/4. Specifically, the following mathematical formula (2):

The time i satisfying the above is recorded as the j-th finger contact point as the following formula (3).

P _j = i (3)
Subsequently, in S4, the interval detection unit 35 calculates the finger contact interval D _j by the following formula (4) based on the finger contact point detected by the contact time detection unit 32.

D _j = P _{j + 1} −P _j (4)
Next, in S _< b> 5, the interval detection unit 35 outputs the finger contact interval D _j to the contact time detection unit 32. If the contact time detection unit 32 determines that the finger contact interval D _j is twice or more the minimum value (Y), the process proceeds to S7. On the other hand, when the contact time detection unit 32 determines that the finger contact interval D _j is not equal to or more than twice the minimum value (N), the process is ended as it is.

  In S7, the contact time detection unit 32 detects the minimum as a finger contact point, and ends the process. In addition, the location where the pulse appears in the acceleration waveform is the finger contact point.

  By the way, in the procedure of the pattern I shown to S1-S4 of FIG. 7, a finger contact point cannot be detected about the finger contact operation | movement with a small acceleration. For this reason, a finger contact interval becomes large. Therefore, it is preferable to detect the finger contact point again using the position waveform for the section where the finger contact interval is large. That is, when the contact time detection unit 32 cannot detect the time when the finger and the finger contact based on the acceleration waveform, the contact time detection unit 32 detects that the finger and the finger are based on the position waveform created by the position waveform creation unit 33. Detect the time of contact. Hereinafter, the procedure of pattern II for detecting finger contact points will be described.

  First, in S6, the contact time detection unit 32 differentiates the position waveform created by the position waveform creation unit 33, which will be described later, with a low-frequency differential filter as shown in the following formula (5).

  Next, in S7, a finger contact point is detected. Specifically, in the contact time detection unit 32, the contact point interval calculated by the interval calculation unit 35 is expressed by the following formula (6):

Find the minimum of the finger contact interval. More specifically, the contact time detection unit 32 has the following mathematical formula (7):

The time i satisfying is added as a finger contact point.

  By this pattern II procedure, finger point contacts that could not be detected by the pattern I processing can be detected. Therefore, the finger contact point can be calculated reliably and efficiently based on the acceleration waveform by the procedure of the above patterns I and II.

As shown in FIG. 7, the processes of the pattern I and the pattern II may be performed in parallel, and as shown in FIG. 21, after the pattern I is performed, the contact time detection unit 32 in S5. However, when it is determined that the finger contact interval D _j is twice or more the minimum value (Y), the process proceeds to S7, pattern II is performed, and the processing for calculating the finger contact interval based on the position waveform can be performed. . These processes can be changed and set as appropriate, and are not limited.

  The position waveform creation unit 33 functions as a position waveform creation unit that creates a position waveform based on the acceleration waveform created by the acceleration waveform creation unit 31. The “position waveform” here is a figure showing the position with the vertical axis and the time (second) with the horizontal axis, and showing the change in the position of the finger that moves over time. As a method for generating the position waveform by the position waveform generation unit 33, for example, a method of generating a position waveform by integrating the acceleration waveform twice can be cited. More specifically, it can be determined by the following methods (i) to (iv). Here, the position waveform was created using only the acceleration waveform based on the signal of the Z-axis component in the acceleration sensor 2 attached to the index finger.

  (i) As shown in the following formula (8), the acceleration is indefinitely integrated according to the trapezoidal rule to obtain the velocity.

  (ii) HPF (cut-off frequency 0.8 Hz) is applied to the speed.

  (iii) Integrate the speed in the same way.

  (iv) The position component at the time of contact between the fingers is corrected to 0 (zero).

  The reaction force calculation unit 34 calculates the reaction force of the finger movement based on the contact time between the finger detected by the contact time detection unit 32 and the signal output from the acceleration sensors 2 and 2. It functions as a calculation means. For example, the reaction force calculation unit 34 is based on the contact time between the finger and the finger detected by the contact time detection unit 32, and the duration of the contact between the finger and the finger (the time during which the finger and the finger are in contact). And the component corresponding to the reaction force can be analyzed by analyzing the acceleration component of the time when the finger is in contact with the finger. More specifically, by estimating the passage of time of the reaction force by applying a low-pass filter process to the signal output from the acceleration sensor within the time when the finger contacts the finger It functions as a reaction force calculation means for calculating the reaction force in the finger movement. The low-pass filter processing is preferably performed at a cutoff frequency in the range of several Hz to several tens Hz. In particular, it is more preferably performed at a cutoff frequency in the range of several Hz to several tens of Hz. In this case, as described later, it is preferable to use a touch sensor and an acceleration sensor in combination. In this case, the duration of contact between the fingers can be easily calculated by the touch sensor.

  The “reaction force” here refers to the reaction force applied to the index finger among the action / reaction forces generated when the finger (mother finger) and the finger (indicating finger) contact each other. Is detected as an acceleration component when touching. The reaction force calculated by the reaction force calculation unit 34 can be used as a new evaluation item for a disease accompanied by movement disorders such as Parkinson's disease in a finger tapping operation, and is highly useful in clinical medicine. Here, the reaction force in the finger tapping operation was calculated based on the signal of the Z-axis component in the acceleration sensor 2 attached to the index finger.

  The interval calculation unit 35 is based on the contact time between the fingers detected by the contact time detection unit 32 (hereinafter referred to as a finger contact point interval or simply a finger contact interval). (Sometimes referred to as “Finger Contact Interval”). The time interval calculated by the interval calculation unit 35, that is, the interval between finger contact points, indicates an irregular rhythm in the finger tapping operation.

  An example of a procedure for calculating the finger contact interval in the interval calculator 35 will be described. The interval calculation unit 35 calculates a finger contact interval based on the finger contact points detected by the contact time detection unit 32. Specifically, it is calculated by the above mathematical formula (4).

  Next, the interval calculation unit 35 obtains the average value of the finger contact intervals by the following mathematical formula (9).

Then, the interval calculation unit 35, the standard deviation _{s D} finger contact interval determined by the following equation (10).

The standard deviation s _D of the finger contact interval can be used as a characteristic amount of irregular rhythm. That is, the interval calculation unit 35 calculates the standard deviation of the interval between the finger-to-finger contact based on the finger-to-finger contact time detected by the contact time detection unit 32, and calculates this as a rhythm irregularity. It can be said that it is output as a feature quantity. The characteristic amount of the rhythm irregularity can be used as a clinical evaluation item of a disease accompanied by movement disorders such as Parkinson's disease in a finger tapping operation, and has high utility value in clinical medicine. Here, the finger contact interval was calculated based on the signal of the Z-axis component in the acceleration sensor 2 attached to the index finger.

  The amplitude calculator 36 calculates the amplitude of the finger motion based on the position waveform created by the position waveform creator 33 and the time when the finger contacts the finger detected by the contact time detector 32. It functions as a means. Here, the “amplitude of finger movement” is the point in the position waveform that is the farthest distance from the straight line connecting two adjacent points among the points where the finger contacts the finger (finger contact point). It means the corresponding maximum amplitude (Max Amplitude) (see FIG. 8). The amplitude calculated by the amplitude calculator 36 indicates the amplitude in the finger tapping operation.

An example of the procedure by which the amplitude calculator 36 calculates the maximum amplitude will be described. The amplitude calculation unit 36 has a maximum amplitude A, where f _j (i) is a straight line connecting adjacent finger contact points, that is, a straight line connecting Z (P _j ) and Z (P _{j + 1} ) in the position waveform. _j is obtained as shown in Equation (11) below.

  The average value of the maximum amplitude is obtained by the following formula (12).

  The average value of the maximum amplitude obtained by the above equation (12) can be considered as a feature quantity of the amplitude of the finger motion in the finger tapping motion. The feature quantity of the amplitude can be used as a clinical evaluation item of a disease accompanied by movement disorder such as Parkinson's disease, and is very useful in clinical medicine. Here, the amplitude in the finger tapping operation is calculated based on the signal of the Z-axis component in the acceleration sensor 2 attached to the index finger.

  Next, regarding the flow of processing in each analysis device 3 when the analysis device 3 calculates the finger contact point interval, the amplitude of the finger movement in the finger tapping, and the reaction force, the functional block diagram and FIG. Description will be made based on the flowcharts 9 (a) to 9 (c).

  First, the case where the analysis device 3 calculates the finger contact point interval will be described with reference to the functional block diagram of FIG. 4 and the flowchart of FIG.

  In S <b> 1, when the subject performs a finger tapping operation, a signal is output to the acceleration waveform creation unit 31 of the analysis device 3 from the acceleration sensors 2 and 2 attached to the subject's thumb and index finger.

  Next, in S2, the acceleration waveform creation unit 31 creates an acceleration waveform based on the signal output from the acceleration sensors 2 and 2.

  Next, when information on the acceleration waveform created by the acceleration waveform creation unit 31 is output to the contact time detection unit 32 in S3, the contact time detection unit 32 performs the acceleration waveform, position waveform, A contact time is detected based on the interval information. At this time, the position waveform is obtained from the position waveform creation section 33 and the interval information is obtained from the interval calculation section 35. As necessary, the contact time is detected based on the position waveform created by the position waveform creation unit 33.

  Subsequently, when the contact time information detected by the contact time detection unit 32 is output to the interval calculation unit 35 in S4, the interval calculation unit 35 calculates the finger contact point interval by the above-described procedure. To do.

  Finally, in S5, the interval calculation unit 35 outputs the calculated interval information to the output device 40 or the information storage device 41 as a rhythm irregular feature amount.

  A case where the analysis device 3 calculates the amplitude of the finger movement in finger tapping will be described with reference to the functional block diagram of FIG. 4 and the flowchart of FIG. 9B.

  First, in S <b> 1, a signal is output from the acceleration sensors 2 and 2 to the acceleration waveform creation unit 31 of the analysis device 3.

  Next, in S2, the acceleration waveform creation unit 31 creates an acceleration waveform based on the signal output from the acceleration sensors 2 and 2.

  Next, when the information of the acceleration waveform created by the acceleration waveform creation unit 31 is output to the position waveform creation unit 33 in S3, the position waveform creation unit 33 performs the above-described procedure based on the acceleration waveform. Create a position waveform.

  Subsequently, in S <b> 4, information on the position waveform created by the position waveform creation unit 33 is output to the amplitude calculation unit 36. Information about the finger point detected by the contact time detection unit 32 is also output to the amplitude calculation unit 36. Then, the amplitude calculation unit 36 calculates the amplitude of the finger movement in finger tapping based on the position waveform and the information of the finger points by the above-described procedure.

  Finally, in S5, the amplitude calculation unit 36 outputs the calculated amplitude information of the finger movement in the finger tapping (as an amplitude feature amount) to the output device 40 or the information storage device 41.

  The case where the analysis device 3 calculates the reaction force of the finger movement in finger tapping will be described with reference to the functional block diagram of FIG. 4 and the flowchart of FIG. 9C.

  First, in S <b> 1, a signal is output from the acceleration sensors 2 and 2 to the acceleration waveform creation unit 31 of the analysis device 3. The signals output from the acceleration sensors 2 and 2 are also output to the reaction force calculation unit 34.

  Next, in S2, the acceleration waveform creation unit 31 creates an acceleration waveform based on the signal output from the acceleration sensors 2 and 2.

  Next, in S3, when the information of the acceleration waveform created by the acceleration waveform creation unit 31 is output to the contact time detection unit 32, the contact time detection unit 32 performs the above procedure based on the acceleration waveform. Detect contact time. At this time, the contact time is detected based on the position waveform created by the position waveform creation unit 33 as necessary.

  Subsequently, when the contact time information detected by the contact time detection unit 32 is output to the reaction force calculation unit 34 in S4, the reaction force calculation unit 34 performs the acceleration sensor 2. Based on the signal output from 2 and the information of the contact time, the reaction force of the finger motion in finger tapping is calculated.

  Finally, in S <b> 5, the reaction force calculation unit 34 outputs the calculated reaction force information of the finger movement in the finger tapping (as a reaction force feature amount) to the output device 40 or the information storage device 41.

[1-3] Touch sensor 6 and analyzer 3 ′
The motion analysis device preferably further includes a touch sensor. Hereinafter, the motion analysis apparatus 1 ′ including the touch sensor 6 will be described with reference to FIG.

  As shown in FIG. 5, the motion analysis device 1 ′ includes two acceleration sensors 2 and 2, two touch sensors 6 and 6, an analysis device 3 ′, an output device 40, and an information storage device 41. The analysis device 3 ′ includes an acceleration waveform creation unit 31, a contact time detection unit 32, a position waveform creation unit 33, a reaction force calculation unit 34, an interval calculation unit 35, and an amplitude calculation unit 36. The description of the same configuration as that described in the section [1-2] will be omitted, and only different parts will be described below.

  The touch sensor 6 may be any sensor that detects contact, and a conventionally known touch sensor can be used, and is not particularly limited. As shown in FIG. 10, the touch sensor 6 is detachably attached to the thumb and the index finger to which the acceleration sensors 2 and 2 are attached. More specifically, in the thumb and index finger to which the acceleration sensors 2 and 2 are attached, the abdomen side of the finger tip, that is, the first joint of the finger and the surface side where the fingerprint is formed (the nail is formed). It is mounted on the back side). That is, the motion analysis apparatus 1 ′ includes two touch sensors 6. In addition, the structure provided with a touch sensor in any one of a thumb or an index finger may be sufficient. In this case, the contact between the thumb and the index finger is detected by this one touch sensor.

  The contact time detection unit 32 in the analysis device 3 ′ detects the time at which the finger contacts the finger tapping operation based on the signal output from the touch sensors 6 and 6. That is, the contact time detection unit 32 does not obtain the contact time by information processing based on the acceleration waveform, the position waveform, and the interval information, but simply determines whether the touch sensor 6 or 6 has touched. -The contact time can be easily obtained based on the output signal of 6. Note that the processing in the analysis apparatus 3 ′ other than this processing is performed in the same manner as in the above [1-2] column.

  As described in the section [1-2] above, the moment at which the finger touches the finger can be detected in the finger tapping operation using the acceleration sensors 2 and 2, but this means that some acceleration is detected. Limited to That is, for example, in a very slow finger tapping operation, the acceleration is too low and contact between the fingers cannot be detected by the acceleration sensor. Therefore, when the operation is very slow, the touch sensor 6 is necessary to detect contact between the fingers. In addition, the touch sensor 6 has an advantage that it can easily detect the moment (time) at which the finger contacts the finger.

  Therefore, by providing the touch sensors 6 and 6, the motion analysis apparatus 1 ′ can reliably detect the contact between the finger and the finger in a very slow finger tapping operation. The contact time can be easily detected.

[1-4] Analysis device 3 "
Further, even a motion analysis device including a touch sensor can detect a contact time between a finger in a finger tapping operation based on both the acceleration sensor and the output signal of the touch sensor. Hereinafter, the motion analysis apparatus 1 ″ will be described with reference to FIG.

  As shown in FIG. 6, the motion analysis device 1 ″ includes two acceleration sensors 2 and 2, two touch sensors 6 and 6, an analysis device 3 ″, an output device 40, and an information storage device 41. The analysis device 3 ″ includes an acceleration waveform creation unit 31, a contact time detection unit 32, a position waveform creation unit 33, a reaction force calculation unit 34, an interval calculation unit 35, and an amplitude calculation unit 36. [1-2] The description of the same configuration as that described in the [1-3] column will be omitted, and only different parts will be described below.

  The contact time detection unit 32 in the analysis apparatus 3 ″ includes the contact time detection unit 32 in the analysis apparatus 3 described in the section [1-2] and the contact time in the analysis apparatus 3 ′ described in the section [1-3]. In other words, the contact time detection unit 32 in the analysis device 3 ″ has the functions of the finger and the interval waveform based on the acceleration waveform, the position waveform, and the interval information. The contact time with the finger is detected. On the other hand, in the case of a very slow tapping operation, the contact time between the fingers can be detected based on the signals output from the touch sensors 6 and 6. It is also possible to detect the contact time between the finger based on the signal output from the touch sensors 6 and 6 in both the case of the normal tapping operation and the case of the very slow tapping operation. is there. In this case, the contact time can be easily calculated based on the output signal of the touch sensor without complicated calculation processing. Needless to say, these functions can be switched as appropriate.

  According to the motion analysis apparatus 1 ″ including such an analysis apparatus 3 ″, it can be used for a subject who performs various operations (relatively fast motion, slow motion, etc.), and has an advantage of high versatility. is there.

[1-5] Output Device and Information Storage Device The output device 40 is a subject obtained by the analysis device 3 (analysis device 3 ′, analysis device 3 ″, hereinafter referred to as the analysis device 3) performing the processing described above. The output device 40 further outputs an acceleration waveform created by the acceleration waveform creation unit 31, a position waveform created by the position waveform creation unit 33, Alternatively, various types of information such as information related to the operation of the analysis apparatus 3 and the like and results of measurement in progress, including the detection result of the contact time detected by the contact time detection unit 32, can be displayed. Various display devices such as CRT displays and liquid crystal displays are preferably used, but are not particularly limited.

  The output device 40 may be provided with a printing unit. The printing means records (printing / image forming) image information that can be displayed by the output device 40 on a recording material such as PPC paper. Specifically, known image forming apparatuses such as an ink jet printer and a laser printer are preferably used, but are not particularly limited. Note that the output device 40 is not limited to the printing unit and the like, and may include other output units.

  The information storage device 41 stores the analysis result of the subject's finger tapping operation obtained by the analysis device 3 or the like performing the above-described processing, and can search and detect it as necessary. Further, the information storage device 41 displays the acceleration waveform created by the acceleration waveform creation unit 31, the position waveform created by the position waveform creation unit 33, the detection result of the contact time detected by the contact time detection unit 32, and the like. In addition, various kinds of information such as information related to the operation of the analysis apparatus 3 and the like and intermediate measurement results may be accumulated.

  In other words, the information storage device 41 functions as a database for storing and managing data quantified by the analysis device 3 or the like. By making the data into a database in this way, it is possible to improve the accuracy and simplification of the determination of treatment effects including clinical trials, realize a uniform medical assistance technology, and use it for medical education. In addition, this database also has an effect of making it possible to easily and quantitatively grasp temporal changes in symptoms of diseases associated with movement disorders such as Parkinson's disease. The information storage device 41 can use a conventionally known means that can be used as a database, and is not particularly limited. For example, an arithmetic device such as a personal computer (PC) or a server can be suitably used.

  Furthermore, the motion analysis device 1 (the motion analysis device 1 ′, the motion analysis device 1 ″, hereinafter referred to as the motion analysis device 1 etc.) according to the present embodiment includes, for example, an input device and a storage device. May be.

  The input device is not particularly limited as long as it can input information related to operations and operations of the analysis device 3 and the information storage device 41, and the like, and a conventionally known input such as a keyboard, a tablet, or a scanner is used. Means can be preferably used. For example, by inputting acceleration waveform data, position waveform data, or the like to the analysis device 3 or the like by the input device, the finger tapping operation can be analyzed more simply.

  The storage device stores various information (data, operation information, control information, calculation results, other information, etc.) used in the analysis device 3 and the information storage device 41. Specifically, for example, semiconductor memories such as RAM and ROM, magnetic disks such as floppy (registered trademark) disks and hard disks, disk systems of optical disks such as CD-ROM / MO / MD / DVD, IC cards (memory cards) Conventionally, various known storage means such as a card system such as an optical card can be suitably used.

  The storage device may be integrated with the analysis device 3 and the information storage device 41 and may be a single device, but may be a separate external storage device. The configuration may include both an integrated storage device and an external storage device. For example, examples of the integrated storage device include a built-in hard disk and a floppy (registered trademark) disk drive, a CD-ROM drive, a DVD-ROM drive and the like incorporated in the device, and an external storage device is an external storage device. Examples include a hard disk and the above-described various disk drives.

  Further, in the above [1-2] to [1-4] column, the motion analysis device including the analysis device for calculating the interval between the finger contact points, the amplitude of the finger motion in finger tapping, and the reaction force has been described. The motion analysis apparatus according to the present invention is not limited to these. That is, for example, a motion analysis device including an analysis device that calculates only one of the finger contact point interval, the finger motion amplitude in the finger tapping, and the reaction force is also included in the present invention. Furthermore, the present invention also includes a motion analysis device including an analysis device that calculates a combination of any two elements of the finger contact point interval, the finger motion amplitude in the finger tapping, and the reaction force.

  In the present embodiment, the motion analysis device in which the acceleration sensor 2 or 2 or the touch sensor 6 or 6 and the analysis device 3 or the like are connected by wire is described. However, the present invention is not limited to this. For example, there is no line between the acceleration sensor 2 or 2 or the touch sensor 6 or 6 and the analysis device 3 or the like, and the acceleration sensor 2 or 2 or the touch sensor 6 or 6 and the analysis device are connected by means of wireless or infrared. An operation analysis apparatus that exchanges information with 3 etc. is also included in the present invention. In such a case, for example, it is preferable that the acceleration sensor 2 or 2 or the touch sensor 6 or 6 includes a data transmitter, and the analysis device 3 or the like includes a data receiver. In this case, there is an advantage that the subject can perform finger tapping operation without worrying about wired connection, which improves wearability, operability, and portability, and makes the device more user-friendly.

  Furthermore, the motion analysis apparatus 1 and the like according to the present embodiment may include a communication device so that various types of information can be input / output via a communication network including the Internet. This communication device is connected to a communication network and can transmit and receive various types of information. For example, the motion analysis apparatus 1 and the like in the same premises, such as a PC and a server, are connected to a communication line to form a bus type LAN (local area network), and this LAN is connected to other areas via the Internet. It may be connected to a certain PC.

  The specific configuration of the communication device is not particularly limited, and a known LAN card, LAN board, LAN adapter, modem, or the like can be suitably used.

  Moreover, about the said PC, the well-known personal computer provided with communication means, such as a modem, can be used conveniently, and it is not limited to a desktop type, a notebook type, etc. Note that the PC has a basic configuration including a display unit such as a CRT display or a liquid crystal display and an input unit such as a keyboard or a mouse. The PC may be provided with hardware (for example, various input means such as a scanner or various output means such as a printer) that can be externally attached to a general personal computer.

  The specific configuration of the server is not particularly limited as long as it is an arithmetic device such as a computer that can provide a service to a PC that is a client constituting the LAN, the operation analysis device 1, and the like. Furthermore, this server may double as a database server or a file server.

  The specific configuration of the communication line is not particularly limited, and a conventionally known general communication line can be used. Also, the type of LAN constructed using this communication line is not limited to the bus type, and may be a conventionally known type such as a star type or a ring type.

  Further, the LAN may include other terminals such as a shared printer. In addition, although not shown, the communication network including the LAN may include various portable terminals capable of communication.

  In the network configured as described above, for example, after analyzing the finger tapping motion of the subject using the motion analysis device 1 or the like, the analysis result is simply output within the motion analysis device 1 or the like (that is, the output device 40 or the like). Alternatively, it can be transmitted to another PC or the like via the LAN. In the PC, the result obtained from the motion analysis apparatus 1 or the like can be displayed on a display unit or printed by a printer, and further, the measurement result can be processed by an input from the input unit. That is, the communication apparatus functions not only as a communication means but also as an input means for inputting information from the remote to the motion analysis apparatus 1 or the like.

  In particular, in the motion analysis device 1 or the like, the acceleration about the finger tapping motion of the subject using the acceleration sensor 2 or 2 or the touch sensor 6 or 6 at a remote place away from the location where the analysis device 3 or the like is located. After obtaining the output signal data of the sensor or the output signal data of the touch sensor, the output signal data of the acceleration sensor or the touch sensor is transmitted to the analysis device 3 or the like existing at a remote place via a network (Internet) using a PC. When sending the output signal data of, or receiving the analysis result of the analysis device 3 or the like after that, the finger tapping operation analysis service is provided to any subject / customer existing in the remote place It becomes possible.

  In addition, when the PC is connected to the motion analysis device 1 or the like via a LAN, for example, if there is one motion analysis device 1 or the like in a medical institution or research facility, other doctors, researchers, etc. The staff can share the motion analysis apparatus 1 and the like via an information terminal such as a PC. Therefore, the present invention can be implemented more efficiently.

  Further, when the server also serves as a database server or a file server, the analysis result of the finger tapping operation performed via the communication network can be accumulated in the server via the communication network. As a result, the sharing of information and the creation of a database proceed, and the analysis results can be used more effectively.

  In addition, in the present invention, it is possible to carry out information processing in the analysis device 3 etc. of the motion analysis device 1 etc. by a program on a computer. The recording medium for recording this program includes Also included is a medium that fluidly carries the program for download from a communication network. For example, if the information processing program in the analysis device 3 or the like is recorded in the recording means of the server, the operation analysis device 1 or the like may download and use the information processing program in the analysis device 3 or the like from the server as appropriate. It may be. However, when the operation analysis device 1 or the like downloads a program from the communication network, the download program is stored in the main body of the analysis device 3 or the like in advance or installed from another recording medium. It has become.

  Further, when connected to a server via a communication network, such as a PC, an information processing program in the analysis device 3 or the like is downloaded from the server, whereby the PC itself is analyzed as an analysis device 3 or the like. 1 or the like.

  Therefore, each block (member, device) of the analysis device 3 and the like according to the present embodiment and the motion analysis device 1 may be configured by hardware logic, or realized by software using a CPU as follows. May be.

  That is, the analysis device 3 and the like include a CPU (central processing unit) that executes instructions of a control program that realizes each function, a ROM (read only memory) that stores the program, and a RAM (random access memory) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is a recording medium on which a program code (execution format program, intermediate code program, source program) of a control program such as the analysis device 3 which is software that realizes the above-described functions is recorded so as to be readable by a computer. It can also be achieved by supplying the data to the analysis device 3 and the like, and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU).

  Examples of the recording medium include a tape system such as a magnetic tape and a cassette tape, a magnetic disk such as a floppy (registered trademark) disk / hard disk, and an optical disk such as a CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.

  Further, the analysis device 3 or the like may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Further, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, infrared rays such as IrDA and remote control, Bluetooth, It can also be used with radio such as 802.11 radio, HDR, mobile phone network, satellite line, and terrestrial digital network. The present invention can also be realized in the form of a carrier wave or a data signal sequence in which the program code is embodied by electronic transmission.

[2] Utilization of Motion Analysis Device As described above, according to the motion analysis device of the present invention, it is possible to quantitatively analyze symptoms of diseases associated with movement disorders such as Parkinson's disease. For this reason, the motion analysis apparatus described in the above section [1] can be used in a determination method for determining the onset of a disease accompanied by movement disorder, the severity of the disease, the evaluation of drug efficacy, or the surgical treatment effect.

  The determination method only needs to use the motion analysis apparatus according to the present invention, and other specific processes, devices, conditions, and the like are not particularly limited. That is, this determination method uses the motion analysis device to analyze the motion of the subject's finger, and based on the analysis result, the onset of the disease with movement disorder, the severity of the disease, the evaluation of the efficacy, or the surgical treatment effect What is necessary is just to judge.

  Conventionally, there was only a qualitative determination means such as subjective evaluation of a skilled doctor. However, according to this determination method, the severity and therapeutic effect of a disease associated with movement disorders such as Parkinson's disease can be quantitatively and easily calculated. Can be determined. This is very useful in clinical medicine from the viewpoint of EBM.

  In addition, the motion analysis apparatus can be used for screening a substance having a therapeutic effect on a disease associated with movement disorders, that is, a drug candidate substance for a disease associated with movement disorders. That is, by using the motion analysis apparatus, it is possible to quantitatively analyze and evaluate a therapeutic effect on a patient with a disorder associated with movement disorder, and thus a substance having a therapeutic effect can be reliably searched for in vivo. .

  The screening method only needs to use the motion analysis apparatus according to the present invention, and other specific steps, equipment, conditions, and the like are not particularly limited. For example, by analyzing the movement of the finger of a Parkinson's disease patient before and after drug administration using the above-described motion analysis apparatus, the therapeutic effect of the drug can be easily evaluated, and the drug can be searched efficiently. In addition, the “disease associated with movement disorder” as used in the present invention refers to a neurological disease in which the motor function is reduced when a nerve is damaged, such as Parkinson's disease.

  Embodiments will be described below in more detail with reference to the accompanying drawings. Of course, the present invention is not limited to the following examples, and it goes without saying that various aspects are possible in detail. Further, the present invention is not limited to the above-described embodiments, and various modifications can be made within the scope shown in the claims, and the present invention is also applied to the embodiments obtained by appropriately combining the disclosed technical means. It is included in the technical scope of the invention.

  The finger tapping motion was analyzed using the motion analysis device according to the present invention. Specifically, it was performed as follows.

  First, as a motion analysis apparatus, as shown in FIG. 1, a three-axis acceleration sensor (manufactured by MicroStone, MA3-20Ab), a power source, an amplifier (amplifier OP491, GAIN1), and an analysis apparatus including a PC were used. Although not shown, an A / D converter (12 bits, sampling frequency 10 kHz) is provided between the amplifier and the PC.

  The experiment was conducted on 7 healthy subjects and 22 patients diagnosed with Parkinson's disease according to the Parkinson's disease diagnostic criteria of the Ministry of Health, Labor and Welfare-specific disease neurodegenerative disease research group. The average age of healthy subjects was 25.5 years, the age range was 22-35 years, and the deviation was 5.88. The average age of Parkinson's disease patients was 69.6 years, the age range was 52-84 years, and the deviation was 8.36. The experiment was performed as shown in FIG.

  The subject was in a sitting position, and the wrist joint to be examined was firmly fixed so that the finger tapping movement surface was almost parallel to the desk. As shown in FIG. 2, a triaxial acceleration sensor was attached to the dorsal side of the distal joint of the thumb and index finger of the hand on the examination side. The opposite movement between the thumb and the index finger, that is, the finger tapping movement, was instructed for 60 seconds as “as large as possible and as quick as possible”, and was performed once for each of the left and right hands. In addition, acceleration X, Y, and Z components were recorded by a PC in accordance with signals output from two three-axis acceleration sensors.

  FIG. 11 shows the created acceleration waveform based on the output signal from the acceleration sensor. Fig. 11 (a) shows an acceleration waveform of a healthy person, and Fig. 11 (b) is a partially enlarged view showing 20 to 22 seconds (region surrounded by a broken line) in Fig. 11 (a). 11C shows an acceleration waveform of a Parkinson's disease patient, and FIG.11D is a partially enlarged view showing 20 to 22 seconds (region surrounded by a broken line) in FIG11C. ), The vertical axis indicates acceleration, and the X-axis, Y-axis, Z-axis of the index finger (Index), and X-axis, Y-axis, and Z-axis acceleration of the thumb (Thumb) in order from the top. As shown to a)-(d), it turned out that the acceleration waveform of a healthy subject and a Parkinson's disease patient differs greatly, and especially the Z-axis component of acceleration differs greatly.

  Next, focusing on the Z-axis component of the finger acceleration, the position waveform was created by integrating the acceleration waveform of the Z-axis component twice. FIG. 12A shows the acceleration waveform before integration, and FIG. 12B shows the position waveform after the second integration. As shown in FIGS. 12A and 12B, it was found that the pulse that is the finger contact portion of the acceleration waveform coincides with the minimum in the position waveform.

  Next, the rhythm irregularity level is shown according to Table 1 below.

  One finger contact interval was calculated for each rhythm irregularity level determined according to Table 1. The rhythm irregularity level 0 is shown in FIG. 13, the rhythm irregularity level 1 is shown in FIG. 14, the rhythm irregularity level 2 is shown in FIG. 15, and the rhythm irregularity level 3 is shown in FIG. (A) of FIGS. 13-16 represents the finger contact interval in time series, the horizontal axis indicates time (s), and the vertical axis indicates the finger contact interval (s). Moreover, (b) of FIGS. 13-16 represents the finger contact interval with a histogram, the horizontal axis represents the finger contact interval (s), and the vertical axis represents the appearance probability (appearance frequency).

  As shown in FIGS. 13 to 16, when the rhythm irregularity level is 0, the finger contact interval variation is small, but as the rhythm irregularity level increases, the finger contact interval variation tends to increase, and the variation is the rhythm irregularity level 3. It turns out that it becomes the maximum in.

  Next, for normal subjects and Parkinson's disease patients, the standard deviation of the finger contact interval and the average value of the maximum amplitude in the finger movement were expressed by a boxplot. A boxplot of the standard deviation of the finger contact interval is shown in FIG. 17, and a boxplot of the average value of the maximum amplitude in the finger movement is shown in FIG. The box in the figure represents between the 25th percentile and the 75% percentile. The center line represents the 50th percentile. The lower end of the whiskers extending from the box represents the 10% percentile, and the upper end represents the 90% percentile. The percentiles above 90% and below 10% are expressed as points as outliers. In the figure, control indicates the value of a healthy person, and Parkinson Disease indicates the value of a Parkinson's disease patient.

  As shown in FIG. 17, patients with Parkinson's disease tend to have larger variations and larger standard deviation values for finger contact intervals than healthy individuals. Further, as shown in FIG. 18, it can be seen that Parkinson's disease patients tend to have a smaller maximum amplitude in finger movement than normal subjects, and the variation is large.

  Next, FIG. 19 shows a box-and-whisker plot of the standard deviation of the finger contact interval for each finger tapping level (UPDRS). The finger tapping level (UPDRS) is shown in Table 2 below.

  As shown in FIG. 19, it was found that as the level increases, the finger contact interval increases and the variation also increases.

  Finally, the component corresponding to the reaction force in the acceleration waveform in the finger tapping operation is schematically shown in FIG. In this experiment, a touch sensor was attached to a finger equipped with an acceleration sensor, and both the acceleration sensor and the touch sensor were used.

  As shown in FIG. 20, in the measured acceleration waveform, an acceleration component corresponding to the reaction force when the finger touches is extracted in addition to the acceleration component accompanying the finger movement. By simultaneously attaching a touch (contact) sensor to a finger, it is possible to detect the duration of contact as shown in FIG. By analyzing the acceleration component during this period, the component corresponding to the reaction force can be analyzed. This may lead to new concepts in clinical evaluation of the main symptoms of Parkinson's disease.

  Since the present invention can quantitatively analyze the symptoms of diseases associated with movement disorders such as Parkinson's disease, it can be used as a medical device useful in clinical medicine. For this reason, it can be used in the medical device industry and the industries associated therewith. Furthermore, the therapeutic effect and the like can be evaluated using the motion analysis apparatus according to the present invention, so that it can be used in the pharmaceutical industry, the food industry, and related industries.

It is a figure which shows typically an example of a structure of the motion analysis apparatus which concerns on this Embodiment. It is a figure which shows typically a mode that the acceleration sensor which concerns on this Embodiment is used. It is a figure which illustrates typically the acceleration detection principle of the acceleration sensor which concerns on this Embodiment. It is a functional block diagram which shows one structural example of the operation | movement analysis apparatus which concerns on this Embodiment. It is a functional block diagram which shows the other structural example of the motion analysis apparatus which concerns on this Embodiment. It is a functional block diagram which shows the other structural example of the motion analysis apparatus which concerns on this Embodiment. It is a flowchart which shows an example of the process for the analysis apparatus which concerns on this Embodiment to calculate the contact time of a finger | toe. It is a figure which shows an example of the process for the analyzer which concerns on this Embodiment to calculate the amplitude in a finger | toe operation | movement. (A) is a flowchart which shows the process for the motion-analysis apparatus which concerns on this Embodiment to calculate a finger contact interval, (b) is the motion-analysis apparatus which concerns on this Embodiment calculates the amplitude in a finger | toe operation | movement. 5 is a flowchart showing a process for calculating a reaction force by the motion analysis apparatus according to the present embodiment. It is an example of the motion analysis apparatus which concerns on this Embodiment, Comprising: It is a figure which illustrates typically a mounting | wearing with a touch sensor and an acceleration sensor. (A) shows an acceleration waveform of a healthy person, (b) is a partially enlarged view showing 20 to 22 seconds (region surrounded by a broken line) in (a), and (c) shows an acceleration waveform of a Parkinson's disease patient. (D) is the elements on larger scale which show 20-22 seconds (area enclosed with a broken line) in (c). (A) shows an acceleration waveform before integration, and (b) shows a position waveform after integration twice. (A) shows the finger contact interval in chronological order for rhythm irregularity level 0, and (b) shows the finger contact interval in a histogram. (A) shows the finger contact interval in time series for the rhythm irregularity level 1, and (b) shows the finger contact interval in a histogram. (A) shows the finger contact interval in chronological order for the rhythm irregularity level 2, and (b) shows the finger contact interval in a histogram. (A) shows the finger contact interval in chronological order for the rhythm irregularity level 3, and (b) shows the finger contact interval as a histogram. It is a box-and-whisker plot showing the standard deviation of the finger contact interval for healthy subjects and Parkinson's disease patients. It is a box-and-whisker diagram showing the average value of the maximum amplitude in the movement of a finger divided into healthy subjects and Parkinson's disease patients. The standard deviation of the finger contact interval for each finger tapping level (UPDRS) is represented by a boxplot. It is a figure which shows typically the component corresponded to reaction force in an acceleration waveform. It is a flowchart which shows another example of the process for the analysis apparatus which concerns on this Embodiment to calculate the contact time of a finger | toe.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Motion analysis apparatus 1 'Motion analysis apparatus 1 "Motion analysis apparatus 2 Acceleration sensor 2a Attachment part (attachment part for thumb mounting)
2b Mounting part (Mounting part for indicating finger)
3. Analysis device (analysis means)
3 'Analysis device (analysis means)
3 "analysis device (analysis means)
6 Touch sensor 31 Acceleration waveform creation unit (acceleration waveform creation means)
32 Contact time detection unit (contact time detection means)
33 Position waveform generator (Position waveform generator)
34 Reaction force calculation unit (reaction force calculation means)
35 Interval calculator (interval calculator)
36 Amplitude calculation unit (amplitude calculation means)

Claims (23)

A motion analysis device for analyzing the motion of a finger of a subject's hand,
A plurality of acceleration sensors detachably attached to each of a plurality of fingers of the subject;
Analyzing means for performing predetermined arithmetic processing on the signal output from the acceleration sensor and analyzing at least one of rhythm irregularity, amplitude, and reaction force in the movement of the finger to which the acceleration sensor is attached; A motion analysis apparatus comprising: The analysis means includes an acceleration waveform creation means for creating an acceleration waveform based on a signal output from the acceleration sensor;
Contact time detection means for detecting a time at which the finger with which the acceleration sensor is attached contacts the finger based on the acceleration waveform created by the acceleration waveform creation means;
2. An interval calculating means for calculating an interval between the time when the finger contacts the finger based on the time when the finger contacts the finger detected by the contact time detecting means. The motion analysis device described in 1. The analysis means includes an acceleration waveform creation means for creating an acceleration waveform based on a signal output from the acceleration sensor;
Contact time detection means for detecting a time at which the finger with which the acceleration sensor is attached contacts the finger based on the acceleration waveform created by the acceleration waveform creation means;
A reaction force calculating means for calculating a reaction force of the finger movement based on a contact time detected by the contact time detection means and a signal output from the acceleration sensor. The motion analysis apparatus according to claim 1. The analysis means includes an acceleration waveform creation means for creating an acceleration waveform based on a signal output from the acceleration sensor;
Contact time detection means for detecting a time at which the finger with which the acceleration sensor is attached contacts the finger based on the acceleration waveform created by the acceleration waveform creation means;
Position waveform creating means for creating a position waveform by integrating the acceleration waveform created by the acceleration waveform creating means twice;
Amplitude calculation means for calculating the amplitude of finger movement based on the position waveform created by the position waveform creation means and the time of contact between the finger detected by the contact time detection means; The motion analysis apparatus according to claim 1, wherein:   The interval calculating means calculates a standard deviation of an interval between the time when the finger contacts the finger based on the time when the finger contacts the finger detected by the contact time detecting means. The motion analysis apparatus according to claim 2.   The reaction force calculating means detects the time of contact between the finger and the finger based on the time when the finger contacts the finger obtained from the contact time detecting means, and the finger is in contact with the finger. The motion analysis apparatus according to claim 3, wherein the reaction force is calculated by analyzing an acceleration component in time.   The reaction force calculation means estimates a time lapse of the reaction force by performing a low-pass filter process on the signal output from the acceleration sensor during the time when the finger is in contact with the finger. The motion analysis apparatus according to claim 6, wherein a reaction force in a finger motion is calculated by doing so.   The motion analysis apparatus according to claim 7, wherein the low-pass filter processing is performed at a cutoff frequency in a range of several Hz to several tens Hz.   In the position waveform, the amplitude calculating means calculates a position of a point that is the furthest away from a straight line connecting two adjacent points among points where the finger is in contact with the finger as the amplitude of the finger movement. The motion analysis apparatus according to claim 4, wherein   The contact time detection means performs a high-pass filter process on the acceleration waveform and performs absolute value detection to detect a time when the finger contacts the finger. The motion analysis apparatus according to any one of 2 to 9. The analysis means further includes position waveform creation means for creating a position waveform by integrating the acceleration waveform created by the acceleration waveform creation means twice.
When the contact time detecting means cannot detect the time when the finger and the finger contact based on the acceleration waveform, the time when the finger and the finger contact based on the position waveform created by the position waveform creating means The motion analysis apparatus according to claim 2 or 3, wherein   When the contact time detecting means cannot detect the time when the finger and the finger contact based on the acceleration waveform, the time when the finger and the finger contact based on the position waveform created by the position waveform creating means The motion analysis apparatus according to claim 4, wherein: Furthermore, the motion analysis device includes a touch sensor that is detachably attached to a finger to which the acceleration sensor is attached.
The acceleration sensor is mounted on the back side of a plurality of fingers,
The motion analysis apparatus according to claim 1, wherein the touch sensor is attached to an abdomen side of a tip portion of a plurality of fingers to which an acceleration sensor is attached. The analysis means includes a contact time detection means for detecting a time at which the finger contacts the finger based on a signal output from the touch sensor;
14. An interval calculating means for calculating an interval between movements of the finger and the finger based on the contact time between the finger detected by the contact time detecting means. The motion analysis device described in 1. The analysis means includes a contact time detection means for detecting a time at which the finger contacts the finger based on a signal output from the touch sensor;
And a reaction force calculating means for calculating a reaction force of the finger movement based on a contact time of the finger detected by the contact time detecting means and a signal output from the acceleration sensor. The motion analysis apparatus according to claim 13. The analysis means includes a contact time detection means for detecting a time at which the finger contacts the finger based on a signal output from the touch sensor;
Acceleration waveform creation means for creating an acceleration waveform based on the signal output from the acceleration sensor;
Position waveform creating means for creating a position waveform by integrating the acceleration waveform created by the acceleration waveform creating means twice;
Amplitude calculating means for calculating the amplitude of finger movement based on the position waveform created by the position waveform creating means and the time of contact between the finger detected by the contact time detecting means; The motion analysis apparatus according to claim 13. The plurality of fingers of the subject's hand are a thumb and an index finger,
At least one of the plurality of acceleration sensors is provided with an attachment portion for attaching a thumb, and at least one of the plurality of acceleration sensors is provided with an attachment portion for attaching a finger. The motion analysis apparatus according to claim 1, wherein The acceleration sensor is a single acceleration sensor that detects accelerations on three axes orthogonal to each other,
The motion analysis according to any one of claims 1 to 17, wherein the analysis unit calculates data based on each signal of the acceleration sensor output corresponding to each axis. apparatus.   The motion analysis apparatus according to claim 1, wherein the finger movement of the subject's hand is a finger tapping operation.   Using the motion analysis device according to any one of claims 1 to 19, determining any of the onset of a disease accompanied by movement disorder, the severity of the disease, the evaluation of drug efficacy, and the surgical treatment effect A determination method characterized by   The determination method according to claim 20, wherein the disease is Parkinson's disease.   A screening method comprising screening a substance having a therapeutic effect on a disease associated with movement disorder using the motion analysis apparatus according to any one of claims 1 to 19.   The screening method according to claim 22, wherein the disease is Parkinson's disease.