State evaluation device for evaluating state of hand

Abstract

To easily evaluate a state of a hand.SOLUTION: A state evaluation device 1 includes: a measurement unit 2 that can be pinched by a first finger and a second finger of a hand; sensors S1 to S4 that are attached to the measurement unit 2; and a signal processing unit 3 that processes signals from the sensors S1 to S4. The signal processing unit 3 evaluates a state of the hand on the basis of the signals from the sensors S1 to S4 in a state where the measurement unit 2 is pinched.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a condition evaluation device for evaluating the condition of a hand. [Background technology]

[0002] Prolonged use of mobile phones and smartphones can cause a condition known as smartphone finger. Smartphone finger is a type of repetitive strain injury (RSI), which occurs when soft tissue is damaged by repeated movements, adversely affecting the flexibility of the fingers and hands, and can cause symptoms such as pain, stiffness, weakness, pain, cramps, and swelling. In the past, RSI patients were often found in workers who performed high-intensity repetitive tasks and professional athletes who exercised a lot, but in recent years, with the spread of smartphones, the number of people suffering from smartphone finger has been increasing.

[0003] The increase in smartphone finger patients is becoming an increasingly common issue for clinicians, and appropriate measures and prevention are required. If smartphone finger becomes chronic, it can severely restrict hand movement and interfere with daily life, so it is important to deal with it at the mild stage when symptoms are not yet apparent. However, the hand is an organ that does not fatigue easily, and it is difficult to discover hidden RSI. For example, Non-Patent Document 1 describes that even medical institutions may not be able to diagnose smartphone finger, especially in the mild stage. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] “How to identify and treat ‘smartphone finger’”, [online], July 23, 2019, Trends, Internet〈URL:https: / / www.m3.com / clinical / open / news / 688739〉 Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention has been made in consideration of the above problems, and an object of the present invention is to easily evaluate the condition of the hand. [Means for solving the problem]

[0006] In order to solve the above problems, the present invention includes the following aspects. Section 1. A measuring unit that can be held between a first finger and a second finger of a hand; A sensor attached to the measurement unit; A signal processing unit that processes a signal from the sensor; Equipped with The signal processing unit evaluates the condition of the hand based on a signal from the sensor when the measuring unit is grasped. Section 2. The measurement unit is a plate-shaped first portion that is in contact with the first finger; a plate-shaped second portion that is in contact with the second finger; Equipped with One end of the first portion and one end of the second portion are connected to each other, The first finger touches the other end of the first portion, Item 2. The condition evaluation device according to item 1, wherein the second finger touches the other end of the second portion. Section 3. Item 2. The condition evaluation device according to item 1, wherein the sensor includes a vibration sensor that detects vibration of the measurement unit. Section 4. Item 2. The condition evaluation device according to item 1, wherein the sensor includes a pressure sensor that detects a pressing force of at least one of the first finger and the second finger against the measuring unit. Section 5. 3. The condition evaluation device according to claim 2, wherein the sensor includes a strain sensor that detects an amount of strain of at least one of the first portion and the second portion. Section 6. Item 2. The condition evaluation device according to item 1, wherein the sensor includes an infrared sensor. Section 7. 7. The condition evaluation device according to item 6, wherein the infrared sensor irradiates infrared light onto the soft tissue between the first finger and the second finger to detect the blood flow rate of the soft tissue. Section 8. 8. The condition evaluating device according to any one of items 1 to 7, wherein the first finger is a thumb and the second finger is an index finger. Section 9. Item 9. The condition evaluation device according to item 8, wherein the signal processing unit evaluates a degree of repetitive fatigue damage as the condition. Effect of the Invention

[0007] According to the present invention, the condition of the hand can be easily evaluated. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration of a condition evaluation device according to an embodiment of the present invention. [Diagram 2] 10(a) to 10(f) are a plan view, a rear view, a left side view, a front view, a bottom view and a perspective view of the measurement part, respectively. [Diagram 3] 13 is a photograph showing the state in which the measuring part is pinched. [Figure 4] 13(a) and (b) are explanatory diagrams of the vibration direction of the measuring unit. [Diagram 5] 4 is a graph showing a waveform of a signal from a vibration sensor. [Figure 6] 4 is a graph showing a waveform of a signal from a pressure sensor. [Figure 7] 4 is a graph showing a waveform of a signal from a strain sensor. [Figure 8] 4 is a graph showing a waveform of a signal from an infrared sensor. [Figure 9] This is a graph showing the distribution of scores for two groups classified by screen time. [Figure 10] This is a graph showing the distribution of finger pain for two groups classified by screen time. [Figure 11] 1 is a graph showing the correlation between score and finger pain. [Figure 12] 1 is a graph showing the correlation between score and screen time. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. Note that the present invention is not limited to the following embodiment, and various modifications are possible without departing from the spirit of the present invention.

[0010] (Overall composition) Fig. 1 is a block diagram showing the configuration of a condition evaluation device 1 according to one embodiment of the present invention. The condition evaluation device 1 includes a measurement unit 2 that can be grasped between the first and second fingers of a hand, sensors S1 to S4 attached to the measurement unit 2, and a signal processing unit 3 that processes signals from the sensors S1 to S4. The sensors provided include a vibration sensor S1, a pressure sensor S2, a strain sensor S3, and an infrared sensor S4. Note that "grasping" means pinching.

[0011] (Measuring section) FIG. 2 shows the configuration of the measurement unit 2, where (a) is a plan view, (b) is a rear view, (c) is a left side view, (d) is a front view, (e) is a bottom view, and (f) is a perspective view. The measurement unit 2 includes a plate-shaped first portion 21 that is in contact with a first finger and a plate-shaped second portion 22 that is in contact with a second finger, and one end 21a of the first portion 21 is connected to one end 22a of the second portion 22. In this embodiment, as shown in FIG. 2(c), the measurement unit 2 is generally in a "L" shape, but is not limited thereto and may be, for example, in a "U" shape. Note that sensors S1 to S4 are omitted in FIG. 2.

[0012] The length of the first portion 21 and the second portion 22 is not particularly limited, but is, for example, 64 mm. The width of the first portion 21 and the second portion 22 is also not particularly limited, but is, for example, 30 mm. The distance between the other end 21b of the first portion 21 and the other end 22b of the second portion 22 is also not particularly limited, but is preferably about the distance between the tip of the thumb and the tip of the index finger when the hand is naturally opened. Since there are individual differences in the size of the hand, it is preferable to prepare a plurality of measuring units 2 of different sizes (for men, women, children, etc.).

[0013] The material of the first part 21 and the second part 22 is not particularly limited, but it is preferable that the first part 21 and the second part 22 have a strength such that they are not irreversibly deformed even if an adult holds the measuring part 2 with all their strength. In this embodiment, the first part 21 is thinner than the second part 22, and has a strength such that the first part 21 bends slightly when an adult holds the measuring part 2 with all their strength. The thickness of the first part 21 is, for example, 5 mm, and the Young's modulus E of the first part 21 is, for example, 2.67 GPa.

[0014] With the measuring unit 2 being pinched, the first finger touches the other end 21b of the first portion 21, and the second finger touches the other end 22b of the second portion 22. In this embodiment, the first finger is the thumb, and the second finger is the index finger, but the first finger and the second finger are not particularly limited.

[0015] 3 is a photograph showing a state in which the measurement unit 2 is being pinched. The thumb touches the other end 21b of the first portion 21, and the index finger touches the other end 22b of the second portion 22. During measurement, the user pinches the measurement unit 2 as tightly as possible and maintains that state.

[0016] (Sensor) Two vibration sensors S1 for detecting vibrations of the measurement unit 2 are provided near the connecting portion between the first portion 21 and the second portion 22. One vibration sensor S1 detects the acceleration of the measurement unit 2 in the horizontal direction (direction X shown in FIG. 4(a)), and the other vibration sensor S1 detects the acceleration of the measurement unit 2 in the vertical direction (direction Y shown in FIG. 4(b)). The position where the vibration sensor S1 is provided is not particularly limited, and for example, the vibration sensor S1 may be provided inside the connecting portion between the first portion 21 and the second portion 22. The number of vibration sensors S1 is not particularly limited, and one vibration sensor may detect vibrations in only one direction.

[0017] A pressure sensor S2 is provided on a portion of first portion 21 that comes into contact with the thumb and a portion of second portion 22 that comes into contact with the index finger. The pressure sensor S2 detects the pressure of the thumb and index finger against measurement unit 2. Although Fig. 3 only shows pressure sensor S2 provided on the portion of first portion 21 that comes into contact with the thumb (the outer surface of the other end 21b), pressure sensor S2 is also provided on the portion of second portion 22 that comes into contact with the index finger (the outer surface of the other end 22b).

[0018] A strain sensor S3 is provided near one end 21a of the first portion 21. As described above, when an average adult pinches the measuring unit 2 with all their strength, the first portion 21 is slightly bent. The strain sensor S3 detects the amount of strain of the first portion 21 when the first portion 21 is bent. The position where the strain sensor S3 is provided is not particularly limited, and it may be provided in the second portion 22.

[0019] Although not shown in Fig. 3, an infrared sensor S4 is provided on the inner surface (the surface on the second portion 22 side) of the other end 21b of the first portion 21. The infrared sensor S4 irradiates the soft tissue between the thumb and index finger with infrared light and detects the blood flow rate of the soft tissue based on the change in the concentration of hemoglobin (Hb) in the capillaries. The wavelength of the infrared light is, for example, 940 nm.

[0020] 5 to 8 are graphs showing waveforms of signals from the vibration sensor S1, the pressure sensor S2, the strain sensor S3 and the infrared sensor S4, respectively. In each graph, the time when the measuring unit 2 starts to grasp is set to 0 s. The signals from the sensors S1 to S4 are input to the signal processing unit 3.

[0021] (Signal Processing Unit) The signal processing unit 3 has a function of evaluating the state of the hand based on signals (hereinafter, sensor signals) from the sensors S1 to S4 when the measuring unit 2 is held. The signal processing unit 3 may be configured with a dedicated computer or a general-purpose computer. Moreover, the signal processing unit 3 may be configured with multiple computers.

[0022] As shown in Fig. 1, the signal processing unit 3 includes a preprocessing unit 31, a signal conditioning unit 32, and an evaluation unit 33. The preprocessing unit 31 performs preprocessing such as filtering the sensor signal by a noise filter, amplifying the filtered sensor signal, and impedance matching. The signal conditioning unit 32 adjusts the preprocessed sensor signal by amplification, division, addition / subtraction, delay processing, or the like. The evaluation unit 33 evaluates the state of the hand based on the sensor signal adjusted by the signal conditioning unit 32.

[0023] The sensor signals are classified into transient state signals and steady state signals. The transient state signal refers to a signal from the moment the finger applies a load to the measuring unit 2 until the bending stress of the first part 21 (the voltage signal from the strain sensor S3) starts to stabilize. The transient state signal indicates the dynamics of the state change. The steady state signal refers to a signal from the moment the bending stress of the first part 21 (the amount of strain detected by the strain sensor S3) starts to stabilize until the soft tissue reaches the limit of damage and the musculoskeletal system of the hand starts to vibrate. During this period, the load on the finger is constant and the bending stress of the first part 21 is stable. After that, the steady state ends due to the damage of the soft tissue, as the hand loses the ability to withstand the load on the finger and irregular movements occur. Therefore, the time of the steady state becomes shorter as the RSI progresses.

[0024] The evaluation unit 33 identifies the time of the steady-state signal from the signal waveform and evaluates the hand condition based on the identified time. For example, the evaluation unit 33 evaluates that there is RSI when the time of the steady-state signal is shorter than a predetermined time (e.g., 10 seconds).

[0025] In addition, because the forces exerted by the thumb and index finger when pinching an object are generated by a multi-jointed musculoskeletal ring, a mechanical model of the fingers can be used to calculate the resultant force from a set of variables, allowing for more precise finger force measurements and therefore a more accurate assessment of the severity of RSI.

[0026] (Summary) As described above, in the condition evaluation device 1, the signal processing unit 3 evaluates the condition of the user's hand based on signals from the sensors S1 to S4 attached to the measurement unit 2 while the measurement unit 2 is held between the first finger and the second finger. The user only needs to hold the measurement unit 2, and the condition evaluation device 1 can be installed not only in medical institutions but also in homes and anywhere else, so that the condition of the user's hand can be easily evaluated. In addition, by holding the finger in a specific controlled mechanical state and observing the biosignal in that state, hidden disorders of the finger can be easily detected. By objectively observing the condition of the finger, it becomes possible to detect problems at an early stage and provide appropriate treatment.

[0027] Moreover, in the condition evaluation device 1, signals from the sensors S1 to S4 are acquired as time-series data. This makes it possible to analyze the magnitude of instantaneous bursts of finger force (sudden generation of force) on the one hand, and to evaluate the ability to continuously output force over a certain period of time on the other hand. Like lifestyle-related diseases, RSI is not cured immediately even with treatment or rehabilitation, and the treatment process takes a long time, requiring continuous observation and evaluation. In contrast, the condition evaluation device 1 is small in size but can acquire highly concentrated information, making it possible to continuously monitor the long-term recovery process of RSI.

[0028] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Forms obtained by appropriately combining the technical means disclosed in the embodiments are also included in the technical scope of the present invention. EXAMPLES

[0029] Examples of the present invention will be described below, but the present invention is not limited to the following examples.

[0030] (Data Collection) In this embodiment, 15 subjects (5 men and 10 women) aged between 22 and 34 were subjected to an investigation into whether the risk of soft tissue injury to the fingers could be appropriately assessed using the condition evaluation device 1 described above.

[0031] First, a preliminary questionnaire was completed to obtain responses from each subject to the following items: 1. Age 2.Gender 3. Smartphone model (OS) 4. Screen time (time spent using smartphone per day) in the past week 5. Finger pain in the past week (VAS) Based on their responses to item 4, participants were divided into two groups: those with more than 3 hours of screen time (>3) and those with less than 3 hours (<3).

[0032] Next, measurements were performed on each subject twice, on May 18, 2024 and June 1, 2024, using the condition evaluation device 1. Specifically, each subject was asked to hold the condition evaluation device 1, and vibration signals, finger pressure signals, strain signals, and near-infrared signals were obtained from the vibration sensor S1, pressure sensor S2, strain sensor S3, and infrared sensor S4, respectively.

[0033] (Calculation of feature values) Based on the collected data, the condition of the subject's hand was evaluated. First, feature quantities were calculated from the signals measured by the sensors S1 to S4 as follows:

[0034] The vibration signal is mainly used to evaluate the limit of the soft tissue of the finger. In this embodiment, the feature quantity F is calculated from the vibration signal based on the following formula: vibration was calculated.

[0035]

number

[0036] Here, V p is a set of peaks of the vibration signal, and N is the number of samples of the signal. In the following, the feature amount calculated from the vibration signal of the vibration sensor S1 that detects vibrations in the horizontal direction is called F vibration1 The feature quantity calculated from the vibration signal of the vibration sensor S1 that detects vibration in the vertical direction is F vibration2 Let us assume that.

[0037] The finger pressure signal is mainly used to evaluate the strength of the finger. In this embodiment, the number of peaks within 80% of the self-maximum value is used as the feature of the finger pressure signal. Specifically, the feature F is calculated based on the following formula: pressure was calculated.

[0038]

number

[0039] Here, P is a data set of all peaks of the finger pressure signal, and p is the peak value. In the following, the feature amount calculated from the finger pressure signal of the thumb pressure sensor S2 is referred to as F pressure1 The feature amount calculated from the finger pressure signal of the index finger pressure sensor S2 is F pressure2 Let us assume that.

[0040] The strain signal is mainly used to evaluate the durability of the finger. In this embodiment, the peak value after the first derivative of the strain signal is used as the feature value. Specifically, the feature value F is calculated based on the following formula: strain was calculated.

[0041]

number

[0042] where S(t) is the value of the strain signal and S'(t) is its first derivative. Note that appropriate noise reduction was performed before extracting the peak value.

[0043] The near-infrared signal is mainly used to evaluate the state of the capillary result. In this embodiment, the average value of the near-infrared signal is used as the feature value. Specifically, the feature value F is calculated based on the following formula: infrared was calculated.

[0044]

number

[0045] Here, I i are the sample values ​​of the infrared signal, and N is the total number of samples excluding missing values.

[0046] Using the above formula, the feature amount of each signal measured by the sensors S1 to S4 was calculated.

[0047] Next, we formulated an evaluation index for soft part injuries of the fingers. Specifically, we calculated a positive feature value and a negative feature value. The positive feature value was calculated using the following formula. Negative Score=0.3×F pressure1 +0.3×F pressure2 +0.3×F strain +0.1×F infrared

[0048] That is, the positive feature value is calculated by taking into account the weighting of the following four signals: Acupressure signal (thumb): 30% Acupressure signal (index finger): 30% Distorted signal: 30% Near infrared signal: 10%

[0049] The negative feature value was calculated using the following formula: Negative Score=0.5×F vibration1 +0.5×F vibration2

[0050] That is, the negative feature value is calculated by taking into account the weighting of the following two signals: Vibration signal (vertical): 50% Vibration signal (horizontal direction): 50%

[0051] The positive and negative feature values ​​calculated in this way were evaluated on a total scale of 100 points to calculate a total score for the soft tissue injury. Total Score=Positive Score+Negative Score

[0052] The overall assessment score is an important indicator of the strength and stability of the fingers, and is used to objectively evaluate the risk of soft tissue injuries in the fingers. In the following, the overall assessment score will be simply referred to as the "score."

[0053] (Data Analysis) Next, we performed data analysis of the evaluation indices calculated as above. Specifically, we calculated basic statistics such as the mean, median, and standard deviation for each group (>3, <3) of the evaluation indices. The basic statistics of screen time, VAS, and score for each subject are shown in Table 1.

[0054] [Table 1]

[0055] We also confirmed the distribution of risk levels (high risk, medium risk, low risk, no risk) for each group. The risk level criteria are shown in Table 2.

[0056] [Table 2]

[0057] In addition, we analyzed the correlation between the evaluation index and risk level, specifically, the correlation between the score and finger pain (VAS), and the correlation between the score and screen time.

[0058] (result) Figure 9 shows the distribution of scores for each of the two groups. An independent T-test revealed a significant difference (p=0.019) in the mean scores between the long screen time group (>3) and the short screen time group (<3). This suggests that prolonged smartphone use may cause soft tissue damage in the fingers, which may affect the scores.

[0059] Figure 10 shows the distribution of finger pain (VAS) for the two groups. For finger pain, the p-value was 0.053, which was slightly below the statistical significance level, but it showed borderline significance. This suggests that the amount of screen time may be somewhat related to finger pain.

[0060] Based on the new evaluation criteria shown in Table 2, the risk levels of the subjects were classified. Of the 15 subjects, 8 were classified as medium risk and 7 were classified as low risk. No subjects were classified as high risk or no risk. The fact that many subjects were classified as medium risk indicates that risk tends to increase when screen time exceeds 3 hours, and it was found that by using the score and the new evaluation criteria, it is possible to quantitatively evaluate the muscle strength and stability of an individual's fingers and classify the risk level. In particular, it was shown that a long screen time is likely to have a negative effect on the health of the hands and fingers. Therefore, it was found that the health risk of an individual's fingers can be detected early by using the condition evaluation device 1 according to the present invention.

[0061] Fig. 11 is a graph showing the correlation between the score and finger pain (VAS). There was a moderate negative correlation (r = -0.297) between the score and finger pain, and subjects with higher scores tended to have less finger pain. This suggests that the condition evaluation device 1 according to the present invention can accurately evaluate the good condition of finger muscle strength and hand stability to a certain extent.

[0062] FIG. 12 is a graph showing the correlation between score and screen time. There was a strong negative correlation (r=-0.807) between score and screen time, and subjects with longer screen time tended to have lower scores. In other words, it was shown that long smartphone usage time is strongly related to reduced finger muscle strength and hand stability. Therefore, it is expected that the condition evaluation device 1 according to the present invention will provide a concrete guideline for more effective hand health management and for reducing damage to the soft tissues of the fingers. [Industrial Applicability]

[0063] The present invention can be applied to the evaluation of not only RSI but also diseases that affect the pinching ability of the fingers, such as carpal tunnel syndrome, stenosing tenosynovitis, De Quervain's disease, and trigger finger. [Explanation of symbols]

[0064] 1 Condition assessment device 2. Measurement section 21 First Part 21a one end 21b Other end 22 Second Part 22a one end 22b other end 3. Signal Processing Section 31 Pretreatment section 32 Signal conditioning unit 33 Evaluation Department S1 Vibration Sensor S2 Pressure Sensor S3 Strain Sensor S4 Infrared Sensor

Claims

1. A measurement unit that can be held between a first finger and a second finger of a hand; A sensor attached to the measurement unit; A signal processing unit that processes a signal from the sensor; Equipped with The signal processing unit evaluates the condition of the hand based on a signal from the sensor when the measuring unit is grasped.

2. The measurement unit is a plate-shaped first portion that is in contact with the first finger; a plate-shaped second portion that is in contact with the second finger; Equipped with One end of the first portion and one end of the second portion are connected to each other, The first finger touches the other end of the first portion, The condition evaluation device according to claim 1 , wherein the second finger contacts the other end of the second portion.

3. The condition evaluation device according to claim 1 , wherein the sensor includes a vibration sensor that detects vibration of the measuring unit.

4. The condition evaluation device according to claim 1 , wherein the sensor includes a pressure sensor that detects a pressing force of at least one of the first finger and the second finger against the measuring portion.

5. The condition evaluation device according to claim 2 , wherein the sensor includes a strain sensor that detects an amount of strain of at least one of the first portion and the second portion.

6. The condition assessment device of claim 1 , wherein the sensor includes an infrared sensor.

7. The condition evaluation device according to claim 6 , wherein the infrared sensor detects a blood flow rate in a soft tissue between the first finger and the second finger by irradiating the soft tissue with infrared rays.

8. The condition evaluation device according to any one of claims 1 to 7, wherein the first finger is a thumb and the second finger is an index finger.

9. The condition evaluation device according to claim 8 , wherein the signal processing unit evaluates a degree of repetitive fatigue damage as the condition.

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