This application claims the foreign priority benefit under Title 35, United States Code, §119(a)-(d) of Japanese Patent Application No. 2006-130124, filed on May 9, 2006 in the Japan Patent Office, the disclosure of which is herein incorporated by reference in its entirety.
1. Field of the Invention
The present invention relates to a moving body inspection apparatus and a method of comparing phases between movement waveforms and particularly to a moving body inspection apparatus for displaying quantitative movement information through analysis of waveforms obtained by a movement sensor.
2. Description of the Related Art
A method of tapping with a finger of a patient is known which quantitatively estimates decrease in a motor function due to motor paralysis. Such a method of tapping for quantitatively estimating the motor function through calculating an average of tapping intervals and a standard deviation, is disclosed by McCombe Waller S, Whitall J., “Fine Motor Control in Adults With and Without Chronic Hemiparesis: Baseline Comparison to Nondisabled Adults and Effects of Bilateral Arm Training” Arch Phys Med Rehabil 85, 1076-1083 (2004).
An aspect of the present invention provides a moving body inspection apparatus comprising: analyzing means for analyzing time series waveform data obtained from a movement sensor, the analyzing means including: movement waveform generating means for generating a plurality of waveforms from the waveform data; and phase comparing means for comparing phases among a plurality of movement waveforms; and displaying means for displaying a result of comparing phases.
According to this structure, a detailed estimation may be provided regarding correlation among a plurality of movements because phases in a plurality of the movement waveforms can be compared.
Another aspect of the present invention provides a method of method of comparing phases among a plurality of the waveforms obtained from a movement sensor, comprising: the steps of: (a) extracting partial waveforms from the waveforms in a frequency analysis time interval having a predetermined time interval; (b) frequency-analyzing the partial waveforms in the frequency analysis time intervals of the waveforms and calculating phases at maximum power frequencies in the frequency analysis time intervals of the partial waveforms; (c) calculating phase differences at the maximum power frequencies in the movement waveforms; and (d) comparing phases among a plurality of the waveforms.
A further aspect of the present invention provides a method of comparing phases among a plurality of the waveforms obtained from a movement sensor, comprising: the steps of: (a) extracting peaks in a plurality of the waveforms; (b) calculating peak time differences between adjoining peaks out of the peaks; (c) matching the peaks among the movement waveforms; (d) calculating time difference among the matched peaks in the movement waveforms; (e) calculating phase differences among the movement waveforms on the basis of the time differences among the matched peaks; and (f) comparing the phases among a plurality of the waveforms.
The object and features of the present invention will become more readily apparent from the following detailed description taken in conjunction with the accompanying drawings in which:
The same or corresponding elements or parts are designated with like references throughout the drawings.
Prior to describing an embodiment of the present invention, the above-mentioned related art will be further explained.
The method disclosed in the above-mentioned prior art document (McCombe Waller S, Whitall J.) cannot analyze difference in phase of tapping timing between both hands in time-series manner. Thus it is difficult to provide correlation of movements of both hands in detail.
The present invention intends to provide a moving body inspection apparatus and a method of comparing phase between movement waveforms in phase.
With reference to drawings will be described preferred embodiments of the present invention.
In a first embodiment, phases are compared among a plurality of movement waveforms through frequency-analyzing for each of a plurality of movement waveforms.
As shown in
A movement sensor 6 for obtaining movement information of a subject as waveform data is connected to the moving body inspection apparatus 1 through the movement sensor interface 3 in the moving body inspection apparatus 1. The movement sensor 6 is a sensor for detecting movement information of the subject and thus any movement sensor can be available as long as it can obtain, as waveform data, movement information of the subject corresponding to at least one of a distance, a velocity, an acceleration, and a jerk.
The “subject” is a target to be measured with the movement sensor 6 and may be anything moving such as a machine, an animal, a human being, and the like. Unless otherwise specified, the embodiments of the present invention exemplifies a case where a subject has a disorder in the motor function such as patients with cerebral infarction, Parkinson's disease patients, and cervical spine losis patients.
In
The coil bobbins 321 and 322 for receiving coil 301 and the transmitting coil 302 are attached to the figures with bands 405 and 406, respectively, in which the bands 405 and 406 are made of elastic member such as a rubber or sponge rubber.
An AC voltage generating circuit 309 generates an AC voltage having a predetermined frequency (for example, 20 kHz). The current generating amplifier circuit 310 converts the AC voltage into an alternating current having the predetermined frequency which is supplied to the transmitting coil 302. The transmitting coil 302 generates a magnetic field according to the alternating current. The generated magnetic field generates an induced voltage in the receiving coil 301.
The induced voltage, having the same frequency as the AC voltage generated by the AC voltage generating circuit 309 is amplified by the preamplifier 303. The amplified signal is applied to a phase shift detector 304.
For detection with the AC voltage, having the predetermined frequency or a double frequency generated by the AC voltage generating circuit 309, the AC voltage of the AC voltage generating circuit 309 is phase-adjusted by a phase adjusting circuit 311, and then, applied to a reference signal input terminal of the phase detector 304 as a reference signal 311A.
In a case that the phase detection is performed with double the predetermined frequency, the phase adjusting circuit 311 is not always necessary. As a simple circuit structure for phase detection with the double frequency, a circuit is usable in which the AC voltage generating circuit 309 is set to the double frequency, which is frequency-divided by two with a frequency divider (not shown). The frequency-divided signal is applied to the current generating amplifier 310. On the other hand, the double frequency is applied to the reference signal input terminal of the phase detector 304.
The output of the phase detector 304 is low-pass-filtered with a low pass filter (LPF) circuit 305 and amplified with an amplifier 306 to have a desired voltage level to generate an output 307. The output 307 represents a voltage corresponding to a relative distance D between the receiving coil 301 and the transmitting coil 302 attached to the subject.
The output 307 is converted into digital data with an analog-to-digital conversion board built in the computer 308 and entered into the computer 308.
In the first and second embodiments of the present invention, the subject has a task of performing a tapping operation, for example, tapping the index finger on the thumb in both hands for 20 seconds as quickly as the subject can (in-phase movement).
Further, the patient is subject to a task of performing a tapping operation, for example, tapping the index finger on the thumb alternately between both hands for 20 seconds as quickly as the patient can (anti-phase movement).
The movement sensor 6 according to the first and second embodiments obtains the movement information as waveform data which can be converted into a distance waveform. In the first and second embodiments, two pieces of the waveform data measured by the tapping devices of the channel one and the channel two are obtained in any task. Thus, the embodiment is described with assumption that “a plurality of pieces of waveform data are obtained by measurement with the tapping devices of the channel one and the channel two in parallel at the same time zone. However, a plurality of pieces of waveform data are unlimited to this in the present invention.
The information processor 2 shown in
The movement sensor interface 3 includes, for example, an analog-to-digital conversion board which may be installed in a general computer to convert the waveform data of an analog signal detected by the movement sensor 6 into a waveform of a digital signal with a predetermined sampling frequency Sf to apply the waveform data of the digital signal to the information processor 2.
Further, the sampling frequency Sf is also used to extract the waveform in the frequency analysis time intervals from the movement waveform (mentioned later).
The display 4 displays the subject information and the movement information processed by the information processor 2. For example, an LCD (Liquid Crystal Display) is usable as the display 4.
The input device 5 is provided for an operator to enter the subject information and instruct the information processor 2 to conduct measurement and analysis and the like. For example, a keyboard and a mouse are usable as the input device 5. In addition, in a case where the operator enters the subject information or the like or instructs the information processor 2 to conduct the measurement and the analysis, it is possible to display an input screen image on the display 4.
The information processor 2 includes an analysis processing section 21, a subject information processing section 22, and a display processing section 23. The information processor 2 is provided with a CPU (Central Processing Unit) and a memory including a ROM (Read Only Memory), a RAM (Random Access Memory) and a hard disk drive and the like. The analysis processing section 21, the subject information processing section 22, and the display processing section 23 operate by that the CPU reads programs and data stored in the memory and the hard disk drive and load the data on the memory to execute the process.
<Analysis Processing Section>
As shown in
<Movement Waveform Generating Part>
The waveform data obtained from the movement sensor 6 is not data directly representing the movement waveform, but an output voltage convertible into a movement waveform.
The movement waveform generating part 211 converts the waveform data as the output voltage into a corresponding movement waveform and performs time differentiation or time integration to complementarily generate a distance waveform, a speed waveform, an acceleration waveform, and a jerk waveform.
The “movement waveform” includes at least one of the distance waveform, the speed waveform, the acceleration waveform, the jerk waveform, and waveforms that can be converted into the four types of the above-mentioned movement waveforms (the distance waveform, the speed waveform, the acceleration waveform, and the jerk waveform). More specifically, the movement waveform to be analyzed by the moving body inspection apparatus 1 is a waveform that can be obtained on the base of the waveform data measured by the movement sensor 6. For example, the waveform may include those measured by the movement sensor 6 or at least one of the four types of the movement waveforms converted or complimentarily generated from the waveform data (the distance waveform, the speed waveform, the acceleration waveform, and the jerk waveform).
A time interval T of the movement waveform is a measurement time of the movement sensor 6. For example, in a case where the tapping movement of the subject is measured for 20 seconds, the time interval T is 20 seconds.
<Phase Comparing Part>
The phase comparing part 212 compares phases among a plurality of movement waveforms obtained on the basis of a plurality of pieces of the waveform data.
In the first embodiment, the phase comparing part 212 conducts a frequency analysis operation for each of a plurality of movement waveforms to calculate and detect a phase of a maximum power spectrum (hereinafter referred to as maximum power frequency) and compares phases among a plurality of the movement waveforms by comparing the maximum power frequencies.
The phase comparing part 212 according to the first embodiment includes a frequency analysis time interval extracting part 212a, a frequency analyzing part 212b, and a phase difference calculating part 212c.
<Frequency Analysis Time Interval Extracting Part>
The frequency analysis time interval extracting part 212a extracts a partial waveform in the movement waveform frequency analysis time interval having a predetermined time interval T0 be frequency-analyzed by the frequency analyzing part 212b.
In this operation, the longer the time interval T0 of the frequency analysis time interval for extraction is extended, the higher the accuracy in the frequency analysis in each frequency analysis time intervals becomes. On the other hand, the shorter the time interval T0 of the frequency analysis time interval for extraction, the finely on time base the information such as the phases of the maximum power frequencies as results of the frequency analysis can be calculated. Thus, it is preferable to select an appropriate length of the time interval T0 of the frequency analysis interval to be extracted. The first embodiment is explained in which the frequency analysis time interval is assumed to be 10 seconds for the movement waveform having duration of 20 seconds.
With reference to
Here, the analysis of the distance waveform is similarly applicable to analyses of the other movement waveforms, and thus, instead of “distance waveform” the term “movement waveform” is used as a dominant conception. Further, the processes of extracting the partial waveforms in the frequency analysis time intervals from the waveform D1(t) of the channel one and the waveform D2(t) of the channel two are the same, and thus, the explanation is made for the movement waveform Dn(t) without any distinction between the waveform D1(t) of the channel one and the waveform D2(t) of the channel two.
First, the frequency analysis time interval extracting part 212a has a discrete expression of the movement waveform Dn(t). The movement waveform Dn(t) discretely expressed can be represented by the following Equation (1).
Dn(t)=Dni (1)
where “n” is channel number, i=1, . . . , LT, and
(the number LT of time intervals of movement waveform)=(the time interval T of the movement waveform)×(sampling frequency Sf).
In
Next, the frequency analysis interval extracting part 212a extracts the partial waveform in the frequency analysis time interval Dnu,i of the predetermined time interval T0 from digitalized waveform Dn. The partial waveform data Dnu,i extracted in the frequency analysis time interval is represented by equation (2).
Dnu,i=Dni (2)
where i=1, . . . , LT0, j=u+i,
(the number u of time intervals up to the frequency analysis time interval)=(the time interval “s” up to the frequency analysis time interval)×(sampling frequency Sf), and
(the number LT0 of time intervals in frequency analysis time interval)=(the time interval T0 of the movement waveform)×(sampling frequency Sf).
In other words, in Equation (2), the partial waveform in the frequency analysis time interval Dnu,i having the predetermined time interval T0 is successively extracted while the frequency analysis time interval Dnu,i is shifted by a time interval (short interval) of 1/(sampling frequency Sf). The partial waveforms Dnu,i in the frequency analysis time intervals extracted by the frequency analysis time interval extracting part 212a are applied to the frequency analyzing part 212b.
<Frequency Analyzing Part>
The frequency analyzing part 212b performs an frequency analysis of the extracted partial waveforms Dnu,i in each frequency analysis time interval and calculates phases of the maximum power frequency in each frequency analysis time interval.
Next, will be described a process of frequency analysis of the partial waveform in the frequency analysis time interval Dnu,i by the frequency analyzing part 212b.
First, the frequency analyzing part 212b calculates power spectrum Anu,k and a phase Θnu,k in each frequency analysis time interval Dnu,i, for example, by a digital Fourier Transform. The process by the digital Fourier Transform is given by Equation (3).
Waveform Dnu,i in Frequency Analysis Time Interval→Power Spectrum Anu,k, Phase Θnu,k (3)
where k=1, . . . , Lf,
(the number Lf of digitizing in frequency base) (LT0/2), and (k/T0=frequency).
Next, the frequency analyzing part 212b obtains the power spectrum Anu,k and phase Θnu,k for each “u” satisfying [0≦u≦LT−LT0].
The frequency analyzing part 212b searches a frequency k of a maximum of the power spectrum Anu,k at each time “u” and sets k(u) to the searched frequency.
Next, the frequency analyzing part 212b determines the phase Θnu,k(u) at the frequency k(u) as the phase Θnu,k of the maximum power frequency at each of time u. At the phase Θnu,k of the maximum power frequency, because “u” is derived by digitizing the time interval (start timing of the frequency analysis time interval) “s” up to the frequency analysis time interval as shown in Equation (2), Θnu=Θn(s), which is represented as the phase waveforms Θn(s) as shown in
The phase 7'n(s) of the maximum power frequency calculated by the frequency analyzing part 212b is applied to the phase difference calculating part 212c.
<Phase Difference Calculating Part>
The phase difference calculating part 212c compares the phases of the maximum power frequency obtained for a plurality of the movement waveforms Dn(t) and calculates a phase difference Θ(s) of the maximum power frequency among a plurality of the movement waveforms.
For example, in a case that phases are compared between two movement waveforms using the movement sensor 6 including tapping devices of the channels one and two, the phase difference Θ(s) at the maximum power frequencies can be obtained from Equation (4).
Phase difference at the maximum power frequencies Θ(s)=(Phase Θ2(s) at Maximum power frequency of Ch2)−(Phase Θ1(s) at Maximum power frequency of Ch1) (4)
The phase difference Θ(s) at the maximum power frequency is shown as a phase difference waveform Θ(s) as shown in
Further, in a phase difference Θ(s) at the maximum power frequencies in more than two movement waveforms, for example, one movement waveform (for example, the phase at the maximum power frequency in the waveform data D1(t) is determined as a reference, and differences between the reference and the phase at of the maximum power frequencies in the waveform data D2(t) and D3(t) are calculated, respectively.
In addition to the phase Θn(s) of the maximum power frequency, the frequency analysis such as a general digital Fourier Transform conducted by the frequency analyzing part 212b can calculate the maximum power frequency and a power at the maximum power frequency.
In other words, the frequency analysis with the moving body inspection apparatus 1 according to the first embodiment provides a power spectrum An (s,f) in each short time interval for each of the movement waveforms as shown in
<Subject Information Processing Section>
Returning to
More specifically, the subject information processing section 22 performs mainly four processes, in combination with the subject data database, including: 1) registration, correction, deletion, searching, and sorting of the subject information; 2) relating the subject information to the movement waveform; 3) registration, correction, and deletion of analysis result of the movement waveform (including addition, correction, and deletion of items); 4) registration, correction, and deletion of results of the statistical processing in a case of conducting statistical processing.
Among subject information registered in the subject data database are a subject ID, a name, a birth date, an age, a body height, a weight, a disease name, a comment regarding the subject and the like.
This information management by the subject information processing section can be easily provided by using well-known programs and data formats.
Further, the subject data database is provided by using a hard disk drive and the like.
<Display Processing Section>
The display processing section 23 displays information such as the subject information and the analysis results of the movement waveforms registered in the subject data database on the display 4 in a display format which is easy to be visually understandable by occasionally using charts and tables. In addition to the generation and displaying the phase waveform Θn(s) and the phase difference waveform Θ(s) shown in
[Method of Comparing Phases]
With reference to
First, the movement waveform generating part 211 in the analyzing processing section 21 sets N=1, before analyzing the waveform data obtained by the “n” channel of the movement sensor 8 (see
Next, the movement waveform generating part 211 in the analyzing processing section 21 generates a movement waveform for time interval T on the basis of the “n” channel of waveform data (step S02). As mentioned earlier, the time interval T is a measurement time interval for the movement sensor 6.
The movement waveform generating part 211 in the analyzing processing section 21 sets s=0, before the frequency analysis time interval extracting part 212a extracts the partial waveform in the frequency analysis time interval after “s” seconds from the start (step S03).
Next, the phase comparing part 212 in the analyzing processing section 21 extracts the partial waveform in the frequency analysis time interval starting after “s” seconds after the start of the waveform for time interval T0 with the frequency analysis time interval extracting part 212a (step S04).
Next, the phase comparing part 212 in the analyzing processing section 21 conducts a frequency analysis operation for the partial waveform in the frequency analysis time interval with the frequency analyzing part 212b to calculate the phase Θn (s) of the maximum power frequency (step S05). For example, the frequency analysis operation is the digital Fourier Transform.
Next, the phase comparing part 212 in the analyzing processing section 21 determines whether s≦T−T0 can be established with the frequency analyzing part 212b (step S06). On the other hand, if s>T−T0 (No, in the step S06), processing proceeds to a step S08.
The phase comparing part 212 in the analyzing processing section 21 determines whether n=total number of channels (step S08). If “n” is not equal to the total number of channels, the phase comparing part 212 sets (n=n+1) (step S09) and returns to the step S02 to repeat the process from the step S02 to the step S09. On the other hand, if “n” is not equal to the total number of channels, the phase comparing part 212 proceeds to a step S10.
The phase comparing part 212 in the analyzing processing section 21 calculates the phase difference Θ(s) at maximum power frequencies between channels with the phase calculating part 212c (step S10). For example, as described above, if the total number of channels is two, the phase difference Θ(s) can be calculated in accordance with Equation (4).
With reference to drawings will be described a second embodiment. In the second embodiment, peaks are extracted for each of the movement waveforms, and phases of the peaks are compared among a plurality of movement waveforms on the basis of the time difference of the peaks.
The second embodiment is different from the first embodiment in the structure of the analysis processing section 21. Thus, in the second embodiment will be mainly described a phase comparing part 312 in the analysis processing section 21, and thus a duplicated description will be omitted.
<Analysis Processing Part>
The phase comparing part 312 according to the second embodiment includes a peak point extracting part 312a, a peak interval calculating part 312b, an inter-channel peak matching part (corresponding to an inter-movement waveform peak matching part) 312c, and a phase difference calculating part 312d.
<Peak Point Extracting Part>
The peak point extracting part 312a extracts peak points (peaks) (1, . . . , Mn; Mn corresponding to the number of the peak points) in the movement waveform.
In
The peak points (1, . . . , Mn) extracted by the peak point extracting part 312a are applied to the peak interval calculating part 312b and the inter-channel peak matching part 312c.
<Peak Time Difference Calculating Part>
The peak interval calculating part 312b calculates a peak time difference which is a difference in time between adjoining peak points in one movement waveform. In
Rni=Pni+1−Pni(i=1, . . . , (Mn−1)) (5)
Next, the peak time difference Rni calculated by the peak time difference calculating part 312b is applied to the phase difference calculating part 312d.
<Inter-Channel Peak Matching Part>
The inter-channel peak matching part 312c is provided for matching peak points among a plurality of movement waveforms.
With reference to
As shown in
More specifically, in
Further, as shown in
Next, the inter-channel peak matching part 312c calculates a time difference between the reference peak point (●) and each of comparison peak points (∘) and selects such one of the comparison peak points (∘) that the time difference is shortest for each reference point to match the peak points between the movement waveforms.
More specifically, the inter-channel peak matching part 312c sets “j” minimizing |P2j−P1i| as m(i) in
Next, information of the peak points matched between the channels is applied to the phase difference calculating part 312d.
In
For example, in a case where the number Mn extracted from more than two movement waveforms, respectively, are the same, the inter-channel peak matching part 312c sequentially matches peak points among the movement waveforms similarly to the case shown in
In addition, for example, in a case where the number of peak points Mn extracted from more than two movement waveforms, respectively, are different, the inter-channel peak matching part 312c determines one peak point of one of more than two movement waveforms as a reference peak point and determines peak points of other movement waveforms as comparison peak points. Next, the inter-channel peak matching part 312c calculates time differences between the reference peak point and the comparison peak points and selects one of the comparison points which provides a minimum time difference from the reference peak point for each reference peak point to match the peak points among the movement waveforms.
<Phase Difference Calculating Part>
The phase difference calculating part 312d calculates phase differences Θi among a plurality of the movement waveforms on the basis of the peak time difference and the time differences of the peak points matched between channels. The phase difference Θi calculated by the phase difference calculating part 312d according to the second embodiment corresponds to an instantaneous phase difference at the peak time (hereinafter, referred to as “instantaneous phase difference”).
For example, in the case where the phases are compared between two movement waveforms obtained with the movement sensor 6 including tapping devices of the channel one and two like the second embodiment, the instantaneous phase difference Θi can be calculated by Equation (6).
Θi=(P2m(i)−P1i)/R1i×360 (6)
The term (P2m(i)−P1i) in Equation (6) represents the time difference of peak points matched between channels (inter-channel time difference).
Further, the instantaneous phase difference Θi among more than two movement waveforms can be calculated by determining an instantaneous phase of one movement waveforms (for example, D1(t)) as a reference and calculating differences from instantaneous phases of other movement waveforms (for example, D2(t),D3(t)).
[Method of Comparing Phases]
With reference to
First, the movement waveform generating part 211 of the analysis processing section 21 sets (n=1) before analyzing the waveform data obtained from the n channels of movement sensor 6 (see
Next, the movement waveform generating part 211 of the analysis processing section 21 generates the movement waveform having the time interval T on the basis of the waveform data of the “n” channel (step S102). Here, as described earlier, the time interval T is generally the measurement time interval by the movement sensor 6.
The phase comparing part 312 of the analysis processing section 21 extracts peak points (1, . . . , Mn; Mn corresponding to the number of peaks) in the movement waveform with the peak point extracting part 312a (step S103).
The phase comparing part 312 in the analysis processing section 21 calculates peak time difference Rni (Rni=Pni+−Pni (i=1, . . . , Mn−1)) from the time difference between peak points adjoining to each other in time in one movement waveform (step S104).
The movement waveform generating part 211 of the analysis processing section 21 determines whether (n the total number of channels) (step S105). If (n≠the total number of channels)(No, in the step S105), the movement waveform generating part 211 returns to step S102 and repeats the process from the steps S102 to S106 until (n=the total number of channels). On the other hand, if (n=the total number of channels) (Yes, in the step S105), the movement waveform generating part 211 proceeds to step S107.
The phase comparing part 312 of the analysis processing section 21 determines whether the number of peak points are identical among a plurality of the movement waveforms with the inter-channel peak matching part 312c (step S107). If the number of peak points are identical (Yes, in step S107), the phase comparing part 312 sets m(i)=i (i=1, . . . , M1) (step S108), and proceeds to a step S110. On the other hand, if the number of peaks are different (No, in step S107), the phase comparing part 312 obtains “j” minimizing |P2j−P1i| and sets m(i)=j (step S109), and proceeds to step S110.
The phase comparing part 312 of the analysis processing section 21 can calculate the instantaneous phase differences among a plurality of the movement waveforms (step S110). Here, as described earlier, the instantaneous phase differences can be calculated with Equation (6). [Example of Display Screen Image]
As shown in
The movement waveform display area 40 displays, for example, the movement waveform 41 obtained in the channel one and the movement waveform 42 obtained by the channel two. This screen image can be displayed on the display 4 by depressing a load-data-file button 43 after measurement with the movement sensor 6. In addition, although not shown in
The type-1 analysis display area 50 is provided for displaying the analysis result according to the first embodiment. For example, the maximum power frequency, the intensity at the maximum power frequency (represented with “MAXIMUM FREQUENCY” in
The type-2 analysis display area 60 is provided for displaying the analysis result according to the second embodiment. For example, the peak time difference, the instantaneous frequency, the instantaneous phase difference, explained in description of the method of calculating in the second embodiment, on the display areas 61 to 63, respectively as sequential charts. This screen image can be made by depressing a do-type-2-analysis button 64 for the second analysis by the operator. More specifically, the information processor 2 including the analysis processing section 21 and the display proceeding part 23 conducts analysis of the movement waveforms 41 and 42 to display the analysis result on the display 4. In addition the information processor 2 calculates an average and a standard deviation of the displayed instantaneous phase difference 63 to display the average and the standard deviation on display areas 65 and 66, respectively.
A phase difference display setting area 70 is provided for setting display formats of the phase difference display areas 54 and 63 displayed in the first analysis display area 50 and the second analysis display area 60. The phase difference display selection button 71 provides selection by the operator as to whether the longitudinal coordinate of the chart in the phase difference display areas 54 and 63 in a range from 0 degrees to 360 degrees or a range from −180 degrees to 180 degrees. This can display the phase difference waveform representing the phase difference at the maximum power frequency or the instantaneous phase difference at centers of the phase difference display areas 54 and 63 in both cases where the in-phase movement and anti-phase movement are analyzed.
The display selecting button 72 for displaying an average line of the phase difference is provided for selection by an operator as whether the average line in the phase difference is to be displayed on the phase difference display areas 54 and 64.
An abnormality display selection button 73 is provided for selection by the operator as to whether an abnormal part is to be displayed, which is caused by determining time zone meeting a predetermined condition (for example, a time zone exceeding a threshold) as an abnormal part. The abnormal part is displayed, for example, with a color different from those in other time zones. This gives the operator visual information which can indicate the part having difficulty in the movement of the subject.
This process of displaying the analysis result on the display 4 can be conducted by the display processing section 23 with well-known programs for the analysis result of the movement waveforms. It is not necessary to display all analysis results on the same screen image. Thus, the display processing section 23 may display any of the analysis results selected by the operator.
Such displaying the analysis results on the display 4 gives an operator information of the motor function of the subject quantitatively and visually.
As described above, according to the first and second embodiments, the phases are compared among a plurality of movement waveforms. Thus, for example, in a case where the task of in-phase movement is applied to the subject, the operator can determine whether the motor function of the subject is normal by checking whether the phases are identical. Further, for example, in a case where the task of the in-phase movement is applied to the subject, the operator can determine whether the motor function of the subject is normal by checking whether the phase difference is always 180 degrees (whether the movements are alternately performed appropriately).
Thus, the moving body inspection apparatus 1 according to the present invention can provide preferable inspection of the motor function of the patients who have the trouble to the motor functions such as patients with cerebral infarction, Parkinson's disease patients, and cervical spine losis patients.
Further, according to the first embodiment, the phases can be compared among a plurality of movement waveforms without extracting peak points from the movement waveforms. More specifically, the analysis is not subject to affection of missing a peak points to be extracted, providing a stable analysis results. In addition, the analysis is performed for the frequency analysis interval having a predetermined time interval, providing the analysis results having low dispersion.
According to the second embodiment, the phase of each extracted peaks can be compared with the other one of a plurality of movement waveforms. In comparing phases, it is unnecessary to set the analysis interval having a predetermined duration, so that the entire time interval T of the measured movement waveform can be used for analysis.
Further, the operations according to the first and second embodiments can be selected or combined in accordance with the object of analysis, which provides a preferable comparison of phases among a plurality of movement waveforms.
This invention is not limited to the above-mentioned embodiments, but can be modified within the scope of the invention.
For example, in addition to outputting the analysis result as the analysis processing section 2 outputs, the analysis result output by the analysis processing section 2 may be subjected to a statistical process before outputting. In this case, a statistical processing section (not shown) is further provided in the information processor 2 which groups the analysis results on the basis of the subject information recorded in the subject data database (not shown) (for example, classifying the subjects into a normal group and a patient group), and conducts the statistical process to output, for example, calculation of averages, variances.
Further, in the first and second embodiments, the analysis such as the phase comparing is conducted after conversion of the output voltages measured by the movement sensor 6. However, the present invention is not limited to this, but the analysis may be conducted directly from the voltage output (waveform data).
In the first and second embodiments, the receiving coil 301 and the transmitting coil 302 in the movement sensor 6 are attached to the thumb and the index finger, but may be attached to any other fingers.
Further, the receiving coil 301 and the transmitting coil 302 may be attached to parts of the human body other than the fingers such as the eyelids, lips, arms, and feet.
In the first and second embodiments, the tapping device of a magnetic sensor type is used as the movement sensor 6, but any other movement sensor 6 is usable as long as the sensor can provide the waveform data indicative of the movement information. For example, the movement sensor 6 may be a well-known strain gage, accelerometer, or speed sensor and further may have a structure for providing the movement information by acquiring image data and analysis of the image data.
In addition, the method of comparing phases with the moving body inspection apparatus 1 can be provided by executing such a program with a general computer using an operating device and a storage in the computer. Thus, this invention is applicable to a program recording the method of comparing phases among a plurality of the movement waveforms.
Number | Date | Country | Kind |
---|---|---|---|
2006-130124 | May 2006 | JP | national |