System and method for predicting tremor conditions

Abstract

A system for predicting tremor conditions is provided, The system comprises: a light emitting unit configured to emits detecting light to illuminate a skin portion of a person in test, the detecting light partially reflected by the skin portion as reflected light and / or the detecting light partially transmitted through the skin as transmitted light; a light sensing unit, configured to receive the reflected light and / or the transmitted light to generate intensity signals in time domain associated with the reflected light and / or the transmitted light; and a signal processing unit, configured to process and analyze the intensity signals in time domain, wherein the signal processing unit transform the intensity signals in time domain to intensity signals in frequency domain by Fast Fourier Transform, and determine if an intensity of the intensity signal in frequency domain in a first pre-set frequency range is greater than a threshold value, so as to determine if the person in test has the tremor conditions.

Description

Technical Field

[0001] This invention relates to a system and method for predicting tremor symptoms, and more particularly to a system and method for predicting tremor symptoms corresponding to Parkinson's disease. Prior Technology

[0002] As physiological signal sensing technology matures, wearable products are becoming increasingly common. Physiological signal sensing can be achieved using optical or ultrasonic sensing architectures. Optical sensing is currently one of the most important development directions in physiological signal sensing technology. For example, pulse, blood pressure, and blood oxygen saturation monitoring in wearable products utilizes optical photoplethysmography (PPG) to analyze physiological signals.

[0003] This invention aims to extend this optical, non-invasive detection method to the prediction of tremor symptoms, particularly tremor symptoms associated with Parkinson's disease. The detection site can be the fingers, wrist, arm, or other possible skin areas. Summary of the Invention

[0004] To effectively solve the aforementioned problems, according to one aspect of the present invention, a tremor symptom prediction system is proposed, comprising: a light-emitting unit configured to emit a detection light to illuminate a skin area of ​​a subject, wherein the detection light is partially reflected by the skin area to form a reflected light, and / or partially transmitted by the skin area to form a transmitted light; a photosensitive unit configured to receive the reflected light and / or the transmitted light to generate an intensity signal of the reflected light and / or the transmitted light in the time domain; and a signal processing unit configured to process and analyze the intensity signal in the time domain, wherein the signal processing unit uses a fast Fourier transform to convert the intensity signal in the time domain into an intensity signal in the frequency domain, and determines whether the intensity of the intensity signal in the frequency domain exceeds a threshold within a first preset frequency range, so as to determine whether the subject has tremor symptoms.

[0005] According to an embodiment of the present invention, preferably, as in the tremor symptom prediction system described above, the first preset frequency range is 4~6Hz.

[0006] According to an embodiment of the present invention, preferably, as in the tremor symptom prediction system described above, the threshold is the maximum value of the intensity signal in the frequency domain within the frequency range of 0.5~3.0Hz or 9~11Hz.

[0007] According to an embodiment of the present invention, preferably, in the tremor symptom prediction system described above, the signal processing unit further analyzes a portion of the intensity signal in the frequency domain within a second preset frequency range to obtain data on heart rhythm and data on blood oxygen saturation, wherein the second preset frequency range is 1.0~1.7Hz, 0.8~2.0Hz, or 0.5~3.0Hz.

[0008] According to an embodiment of the present invention, preferably, in the tremor symptom prediction system described above, the photosensitive unit is a photodiode image sensor, a complementary metal-oxide-semiconductor image sensor, a charge-coupled device image sensor, or a combination thereof, and the detection light is blue light, green light, red light, infrared light, or a combination thereof.

[0009] According to one aspect of the present invention, a wearable device is proposed that includes the above-described tremor symptom prediction system.

[0010] According to one aspect of the present invention, a method for predicting tremor symptoms is proposed, wherein the method uses a tremor symptom prediction system, the tremor symptom prediction system comprising a light-emitting unit, a photosensitive unit, and a signal processing unit, the method comprising: using the light-emitting unit to emit a detection light to illuminate a skin area of ​​a subject, the detection light being partially reflected by the skin area to form a reflected light, and / or partially transmitted by the skin area to form a transmitted light; using the photosensitive unit to receive the reflected light and / or the transmitted light, the photosensitive unit generating an intensity signal of the reflected light and / or the transmitted light in the time domain; and using the signal processing unit to process and analyze the intensity signal in the time domain, wherein the step of processing and analyzing the intensity signal in the time domain comprises: using a fast Fourier transform to convert the intensity signal in the time domain into an intensity signal in the frequency domain, and determining whether the intensity of the intensity signal in the frequency domain exceeds a threshold within a first preset frequency range, to determine whether the subject has tremor symptoms.

[0011] According to an embodiment of the present invention, preferably, as described in the above-described method for predicting tremor symptoms, the first preset frequency range is 4~6Hz.

[0012] According to an embodiment of the present invention, preferably, as described in the above-described method for predicting tremor symptoms, the threshold is the maximum value of the intensity signal in the frequency domain within the frequency range of 0.5~3.0Hz or 9~11Hz.

[0013] According to an embodiment of the present invention, preferably, in the above-described method for predicting tremor symptoms, the step of processing and analyzing the intensity signal in the time domain further includes: analyzing a portion of the intensity signal in the frequency domain within a second preset frequency range to obtain data on heart rhythm and data on blood oxygen saturation, wherein the second preset frequency range is 1.0~1.7Hz, 0.8~2.0Hz, or 0.5~3.0Hz.

[0014] According to an embodiment of the present invention, preferably, in the tremor symptom prediction method described above, the photosensitive unit is a photodiode image sensor, a complementary metal-oxide-semiconductor image sensor, a charge-coupled device image sensor, or a combination thereof, and the detection light is blue light, green light, red light, infrared light, or a combination thereof.

[0015] According to an embodiment of the present invention, preferably, as described above in the tremor symptom prediction method, the tremor symptom prediction system is included in a wearable device.

[0016] To enable those skilled in the art to understand the purpose, features and effects of the present invention, the present invention will be described in detail below with reference to the following specific embodiments and accompanying drawings. Simple Explanation of the Diagram

[0017] Figure 1 is a graph of intensity signal versus time in the time domain according to an embodiment of the present invention; Figure 2 is a graph of intensity signal versus frequency in the frequency domain according to an embodiment of the present invention; Figure 3 is a block diagram of a tremor symptom prediction system according to the present invention; and Figure 4 is a flowchart of a tremor symptom prediction method according to the present invention. Implementation

[0018] Optical photoplethysmography (PPG) is a non-invasive method for detecting changes in blood volume in living tissue using photoelectric techniques. When a beam of light of a certain wavelength shines on the skin surface of the fingertip, the contraction and expansion of blood vessels due to the heartbeat affect the transmission (e.g., light passing through the fingertip in a transmissive PPG) or the reflection (e.g., light from near the wrist surface in a reflective PPG). When light passes through skin tissue (e.g., the skin tissue of the fingers, including subcutaneous tissue, microvascular tissue, etc.) and is then reflected and / or transmitted to the photosensitive element, the light intensity will attenuate and change over time because the blood volume and blood oxygen saturation in the microvessels change with the pulse. By analyzing the changes in the transmitted or reflected light signals using corresponding algorithms, physiological data such as pulse, blood pressure, and / or blood oxygen saturation can be obtained. Details of related prior art techniques will not be elaborated here.

[0019] Research and testing have shown that hand tremors also affect the signal changes of transmitted and reflected light in the aforementioned optical photoplethysmography. Therefore, the prediction of tremor symptoms, especially those related to Parkinson's disease, can be achieved using optical photoplethysmography and can be applied to wearable devices.

[0020] The technical content of the present invention will be described below with reference to the accompanying drawings.

[0021] Figure 1 is a graph of intensity signal versus time in the time domain according to an embodiment of the present invention; Figure 2 is a graph of intensity signal versus frequency in the frequency domain according to an embodiment of the present invention; and Figure 3 is a block diagram illustrating a tremor symptom prediction system according to an implementation of the present invention.

[0022] Please refer to Figure 1. According to an embodiment of the present invention, the signal of reflected or transmitted light reflected or transmitted through the skin tissue of the subject's hand (e.g., the skin tissue of the fingers, wrist, etc.) using the photovolume change mapping method can be as shown in Figure 1. Figure 1 shows a graph of the intensity signal versus time in the time domain, with the horizontal axis representing time and the vertical axis representing intensity. The unit of intensity can be any unit (relative quantity comparison) or a unit of light intensity (e.g., light intensity, illuminance, etc.), but the present invention is not limited thereto.

[0023] Please refer to Figure 2. According to an embodiment of the present invention, the intensity signal versus time curve in the time domain shown in Figure 1 can be converted into the intensity signal versus frequency curve in the frequency domain shown in Figure 2 by Fast Fourier Transform (FFT). The horizontal axis represents frequency and the vertical axis represents intensity. The unit of intensity can be any unit (relative quantity comparison) or number of times (counting), but the present invention is not limited thereto.

[0024] According to current knowledge and relevant literature, the frequency of hand tremors associated with Parkinson's disease falls approximately in the range of 4-6 Hz, as shown in Figure 2, while general physiological tremors (e.g., hand tremors in the elderly) fall approximately in the range of 9-11 Hz. Therefore, intensity signal data within the 4-6 Hz frequency range can be analyzed; alternatively, intensity signal data within the 0.5-3.0 Hz, 4-6 Hz, and 9-11 Hz frequency ranges can be analyzed simultaneously. The intensity signal data within the 0.5-3.0 Hz and 9-11 Hz frequency ranges can be used as control or comparative data to improve the accuracy of the tremor symptom prediction system and method of this invention. The aforementioned 0.5-3.0 Hz frequency range corresponds to the heart rate.

[0025] According to embodiments of the present invention, whether a subject has tremor symptoms related to Parkinson's disease can be determined by determining whether the intensity signal in the frequency domain exceeds a preset threshold value within the frequency range of 4 to 6 Hz. The threshold value can be arbitrarily adjusted according to the required sensitivity or accuracy of the judgment or prediction. For example, if the intensity signal in the frequency domain exceeds the preset threshold value within the frequency range of 4 to 6 Hz, it can be determined that the subject has tremor symptoms related to Parkinson's disease.

[0026] Additionally, determining whether a subject exhibits tremor symptoms associated with Parkinson's disease can be achieved by checking whether the maximum intensity of the signal in the 4-6 Hz frequency range exceeds the maximum intensity in the 9-11 Hz frequency range. For example, if the maximum intensity of the signal in the 4-6 Hz frequency range exceeds the maximum intensity in the 9-11 Hz frequency range, the subject can be diagnosed with tremor symptoms associated with Parkinson's disease. Alternatively, a weighted comparison can be used to compare the maximum intensity of the signal in the 4-6 Hz frequency range with the maximum intensity in the 9-11 Hz frequency range to determine if the subject exhibits tremor symptoms associated with Parkinson's disease.

[0027] Additionally, the presence of tremor symptoms associated with Parkinson's disease can be determined by checking whether the maximum intensity of the signal in the frequency domain within the 4–6 Hz range exceeds the maximum intensity in the 0.5–1.5 Hz, 0.5–2.0 Hz, 0.5–2.5 Hz, or 0.5–3.0 Hz ranges. For example, if the maximum intensity of the signal in the frequency domain within the 4–6 Hz range exceeds the maximum intensity in the 0.5–1.5 Hz range, the subject can be diagnosed with tremor symptoms associated with Parkinson's disease. Alternatively, a weighted comparison can be used to compare the maximum intensity of the signal in the 4–6 Hz range with the maximum intensity in the 0.5–1.5 Hz range to determine if the subject has tremor symptoms associated with Parkinson's disease.

[0028] Referring to Figure 3, according to an embodiment of the present invention, the tremor symptom prediction system 100 of the present invention may include a light-emitting unit 110, a light-sensing unit 120, and a signal processing unit 130, wherein the light-emitting unit 110 and the light-sensing unit 120 may be electrically connected to the signal processing unit 130.

[0029] The light-emitting unit 110 of the present invention may include one or more light-emitting elements for emitting detection light to illuminate the skin area of ​​the subject (such as the skin area of ​​the fingers, wrist, arm, etc.), so that the detection light is reflected and / or transmitted to form reflected and / or transmitted light. The light-emitting element may be a light-emitting diode, a miniature light-emitting diode, an organic light-emitting diode, or a combination thereof, but the present invention is not limited thereto. Users can arbitrarily select the type of light-emitting element according to their needs, and using multiple types of light-emitting elements simultaneously can improve the reliability of symptom assessment. The detection light may be blue light, green light, red light, infrared light, or a combination thereof, but the present invention is not limited thereto. Users can arbitrarily select the wavelength range of the detection light according to their needs, and using multiple wavelength ranges of detection light simultaneously can improve the reliability of symptom assessment. For example, users can consider factors such as blood having a stronger reflection of red light and a stronger absorption of blue light, and red blood cells with higher oxygen content having a higher reflection of red light than red blood cells with lower oxygen content, etc., to select the wavelength range of the detection light.

[0030] The photosensitive unit 120 of the present invention may include one or more photosensitive elements for receiving reflected and / or transmitted light from the skin area to generate an intensity signal of the reflected and / or transmitted light in the time domain. For example, the photosensitive unit 120 may include a single photosensitive element for receiving reflected or transmitted light from the skin area. Alternatively, the photosensitive unit 120 may include multiple photosensitive elements disposed at different locations to simultaneously receive reflected and transmitted light from the skin area. The photosensitive element may be a photodiode image sensor, a complementary metal-oxide-semiconductor image sensor, a charge-coupled device image sensor, or a combination thereof, but the present invention is not limited thereto. Users can arbitrarily select the type of photosensitive element according to their needs, and using multiple types of photosensitive elements simultaneously can improve the reliability of symptom diagnosis. For example, when using different light-emitting elements, detection wavelength ranges, and / or photosensitive elements simultaneously, the results obtained by averaging, weighting, etc., the corresponding different data can be used as the basis for symptom diagnosis.

[0031] The signal processing unit 130 of the present invention may include a processor and memory. After receiving a signal generated by the photosensitive unit 120, it processes and analyzes the intensity signal in the time domain. The signal processing unit 130 of the present invention can generate, process, and analyze the intensity signal in the time domain after receiving a signal generated by the photosensitive unit 120. The memory may store algorithms for performing calculations related to photoplethysmography and for analyzing, judging, and predicting tremor symptoms. The signal processing unit 130 can convert the intensity signal in the time domain generated by the photosensitive unit 120 into an intensity signal in the frequency domain using a fast Fourier transform, and further determine whether the intensity of the intensity signal in the frequency domain exceeds a preset threshold in a first preset frequency range (e.g., a frequency range of 4-6 Hz) to determine whether the subject has tremor symptoms related to Parkinson's disease. Alternatively, the signal processing unit 130 can analyze and confirm whether the intensity of the signal in the frequency domain is higher in the frequency range of 4-6 Hz than in the frequency range of 9-11 Hz, in order to determine whether the subject has tremor symptoms related to Parkinson's disease. According to embodiments of the present invention, the first preset frequency range can also be selected as 4-5 or 5-6 Hz to improve the accuracy of symptom judgment; or the first preset frequency range can also be selected as 3-6, 4-7, or 3-7 Hz to improve the sensitivity of symptom judgment.

[0032] According to embodiments of the present invention, the tremor symptom prediction system of the present invention can further have the function of detecting the heart rhythm and blood oxygen saturation of the subject, so as to achieve the effect of single-unit multi-functionality and multi-purpose use. The signal processing unit of the tremor symptom prediction system can further analyze the intensity signal in the frequency domain within a second preset frequency range to obtain data on heart rhythm and data on blood oxygen saturation, wherein the second preset frequency range can be 1.0~1.7Hz, 0.8~2.0Hz, or 0.5~3.0Hz, corresponding to the frequency range of heart rhythm.

[0033] According to an embodiment of the present invention, the tremor symptom prediction system of the present invention may further include a transmission unit for transmitting relevant data and results of detection or prediction (e.g., information on whether tremor symptoms are present, information on pulse or heart rhythm, information on blood oxygen saturation, etc.) to an external device.

[0034] According to embodiments of the present invention, the tremor symptom prediction system of the present invention may further include a display unit for displaying relevant data and results of detection or prediction (e.g., information on whether tremor symptoms are present, information on pulse or heart rhythm, and / or information on blood oxygen saturation, etc.) to instantly grasp the relevant physiological state of the subject.

[0035] Next, we will describe the method of using the tremor symptom prediction system of the present invention.

[0036] Referring to Figure 4, according to an embodiment of the present invention, the tremor symptom prediction method of the present invention includes the following steps. First, step S10: using a light-emitting unit to emit detection light to illuminate the skin area of ​​the subject, the detection light is partially reflected by the skin area to form reflected light, and / or partially transmitted by the skin area to form transmitted light. Step S20: using a photosensitive unit to receive the reflected light and / or the transmitted light, the photosensitive unit generates an intensity signal in the time domain regarding the reflected light and / or the transmitted light. Step S30: using a signal processing unit to convert the intensity signal in the time domain into an intensity signal in the frequency domain using a fast Fourier transform. Finally, step S40: using a signal processing unit to determine whether the intensity of the intensity signal in the frequency domain exceeds a threshold in a first preset frequency range, to determine whether the subject has tremor symptoms. Related details are as previously described in the description of the tremor symptom prediction system of the present invention, and will not be repeated here.

[0037] The tremor symptom prediction system and method of the present invention can be implemented in wearable devices. For example, the tremor symptom prediction system of the present invention can be included in smart rings, smart bracelets, smart earrings, etc., but the present invention is not limited to this. Any part of the subject's skin can be the detection site of the corresponding wearable device containing the tremor symptom prediction system of the present invention.

[0038] The above description illustrates the implementation of the present invention through specific embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

[0039] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of the present invention; any equivalent changes or modifications made without departing from the spirit disclosed in the present invention should be included within the scope of the following patent.

[0040] 100: Tremor Symptom Prediction System

[0041] 110: Light-emitting unit

[0042] 120: Photosensitive unit

[0043] 130: Signal Processing Unit

[0044] S10: Steps

[0045] S20: Steps

[0046] S30: Steps

[0047] S40: Steps

Claims

1. A tremor symptom prediction system, comprising: a light-emitting unit configured to emit a detection light to illuminate a skin area of ​​a subject, the detection light being partially reflected by the skin area to form reflected light, and / or partially transmitted by the skin area to form transmitted light; a photosensitive unit configured to receive the reflected light and / or the transmitted light to generate an intensity signal of the reflected light and / or the transmitted light in a time domain; and a signal processing unit configured to process and analyze the intensity signal in the time domain, wherein... The signal processing unit uses a fast Fourier transform to convert the intensity signal in the time domain into an intensity signal in the frequency domain, and determines whether the intensity of the intensity signal in the frequency domain exceeds a threshold in a first preset frequency range, in order to determine whether the subject has the tremor symptoms.

2. The tremor symptom prediction system as described in claim 1, wherein, The first preset frequency range is 4~6 Hz.

3. The tremor symptom prediction system as described in claim 2, wherein, This threshold is the maximum value of the intensity signal in the frequency domain within the frequency range of 0.5~3.0 Hz or 9~11 Hz.

4. The tremor symptom prediction system as described in claim 2, wherein, The signal processing unit further analyzes a portion of the intensity signal in the frequency domain within a second preset frequency range to obtain data on heart rhythm and blood oxygen saturation, wherein the second preset frequency range is 1.0~1.7 Hz, 0.8~2.0 Hz, or 0.5~3.0 Hz.

5. The tremor symptom prediction system as described in claim 1, wherein, The photosensitive unit is a photodiode image sensor, a complementary metal-oxide-semiconductor image sensor, a charge-coupled device image sensor, or a combination thereof, wherein the detection light is blue light, green light, red light, infrared light, or a combination thereof.

6. A wearable device comprising: a tremor symptom prediction system as described in any one of claims 1 to 5.

7. A method for predicting tremor symptoms, wherein, The method uses a tremor symptom prediction system, which includes a light-emitting unit, a photosensitive unit, and a signal processing unit. The method includes: using the light-emitting unit to emit a detection light to illuminate a skin area of ​​a subject, wherein the detection light is partially reflected by the skin area to form a reflected light, and / or partially transmitted by the skin area to form a transmitted light; using the photosensitive unit to receive the reflected light and / or the transmitted light, wherein the photosensitive unit generates an intensity signal of the reflected light and / or the transmitted light in the time domain. The signal processing unit is used to process and analyze the intensity signal in the time domain, wherein the step of processing and analyzing the intensity signal in the time domain includes: using a fast Fourier transform to convert the intensity signal in the time domain into an intensity signal in the frequency domain, and determining whether the intensity signal in the frequency domain exceeds a threshold in a first preset frequency range, so as to determine whether the subject has the tremor symptoms.

8. The method for predicting tremor symptoms as described in claim 7, wherein, The first preset frequency range is 4~6 Hz.

9. The method for predicting tremor symptoms as described in claim 8, wherein, This threshold is the maximum value of the intensity signal in the frequency domain within the frequency range of 0.5~3.0 Hz or 9~11 Hz.

10. The method for predicting tremor symptoms as described in claim 8, wherein, The step of processing and analyzing the intensity signal in the time domain further includes: analyzing a portion of the intensity signal in the frequency domain within a second preset frequency range to obtain data on heart rhythm and data on blood oxygen saturation, wherein the second preset frequency range is 1.0~1.7 Hz, 0.8~2.0 Hz, or 0.5~3.0 Hz.

11. The method for predicting tremor symptoms as described in claim 7, wherein, The photosensitive unit is a photodiode image sensor, a complementary metal-oxide-semiconductor image sensor, a charge-coupled device image sensor, or a combination thereof, wherein the detection light is blue light, green light, red light, infrared light, or a combination thereof.

12. The method for predicting tremor symptoms as described in any one of claims 7 to 11, wherein, The tremor symptom prediction system is contained in a wearable device.

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