CN-121971804-A - Acupuncture point stimulation system based on artificial intelligence

CN121971804ACN 121971804 ACN121971804 ACN 121971804ACN-121971804-A

Abstract

The invention relates to the technical field of intelligent medical treatment, in particular to an acupoint stimulation system based on artificial intelligence, which comprises the steps of acquiring a strain value generated by contact of an acupoint electrode with skin through a data extraction module, controlling each acupoint electrode to be in a pre-output state through a stimulated evaluation module, and screening stimulated acupoints in the pre-output state; and judging whether the first stimulation parameters are qualified or not or determining the second output parameters based on the stimulated conditions through the positioning and adjusting module. Furthermore, the dynamic parameter adjustment mechanism is generated based on the physiological signals and muscle response characteristics of the human body, and the accuracy and the intellectualization of the acupoint stimulation process are improved according to the physiological association among different acupoints in the multi-acupoint collaborative stimulation scene.

Inventors

QU YUAN
Chi Yenan
CHANG FEIFEI
ZHANG JINQIANG

Assignees

中国中医科学院广安门医院

Dates

Publication Date: 20260505
Application Date: 20260401

Claims (10)

1. An artificial intelligence based acupoint stimulation system, comprising: A plurality of acupoint electrodes for outputting alternating current to stimulate acupoints; the data extraction module comprises a plurality of muscle strain acquisition units distributed around each acupoint electrode for acquiring strain values generated by the contact of the acupoint electrode with skin and a heart rate acquisition unit for acquiring heart rate signals of a human body and calculating heart rate variability; The stimulated evaluation module is respectively connected with the acupuncture point electrodes and the data extraction module and is used for controlling each acupuncture point electrode to be in a pre-output state and screening stimulated acupuncture points according to the strain value comparison condition of the muscle strain acquisition units distributed around each acupuncture point electrode in the pre-output state; The intelligent analysis module is connected with the stimulated evaluation module and used for determining the associated stimulated conditions of the stimulated acupuncture points according to the stimulated expression of the stimulated acupuncture points; The positioning adjustment module is connected with the intelligent analysis module and is used for adjusting the stimulation parameters based on the associated stimulated conditions, and comprises judging whether the first stimulation parameters are qualified or not according to heart rate variability, or determining a plurality of collaborative stimulation acupoint sets according to stimulated performance, respectively determining local characteristic performance for the acupoints in each collaborative stimulation acupoint set and determining a second output parameter according to the distribution relation of the acupoints in the collaborative stimulation acupoint sets; Wherein each co-stimulatory acupoint set comprises a plurality of stimulated acupoints which are stimulated to have the same performance.
2. The artificial intelligence based acupoint stimulation system of claim 1, wherein the stimulated assessment module is configured to plot a muscle response curve, wherein, The stimulated evaluation module establishes a rectangular coordinate system by taking a strain value as a vertical axis and taking time as a horizontal axis, and draws a muscle response curve of the strain value of the muscle strain acquisition units distributed around each acupoint electrode along with time in the rectangular coordinate system; The stimulated evaluation module is further used for determining the curve area enclosed by the muscle response curve corresponding to each muscle strain acquisition unit and the transverse axis in a preset pre-output period, and determining the curve area as a stimulated response characterization quantity.
3. The artificial intelligence based acupoint stimulation system of claim 2, wherein the stimulated assessment module is configured to screen stimulated acupoints, wherein, The stimulated evaluation module is used for calculating standard deviations of stimulation response characterization quantities corresponding to a plurality of muscle strain acquisition units distributed around the current acupoint electrode; If the standard deviation meets the capturing and screening conditions, the stimulated evaluation module screens the current acupoint electrode as a stimulated acupoint; The capture screening condition is that the standard deviation is larger than a preset standard deviation threshold.
4. The artificial intelligence based acupoint stimulation system of claim 3, wherein the intelligent analysis module is configured to screen the characteristic dominant acquisition units among the muscle strain acquisition units distributed around the stimulated acupoint, wherein, The intelligent analysis module is used for screening a characteristic dominant acquisition unit according to a time sequence of a first extreme point of a muscle response curve corresponding to the muscle strain acquisition units distributed around the stimulated acupuncture points; The muscle response curve corresponding to the characteristic dominant acquisition unit is first provided with a first extreme point in time sequence.
5. The artificial intelligence based acupoint stimulation system of claim 4, wherein the intelligent analysis module is configured to determine the stimulated behavior of each stimulated acupoint, wherein, The intelligent analysis module takes the acupoint electrode as a vector starting point, takes the characteristic dominant acquisition unit as a vector end point to construct a stimulated offset unit vector, and determines the vector direction of the stimulated offset unit vector as the stimulated expression of the stimulated acupoint.
6. The artificial intelligence based acupoint stimulation system of claim 5, wherein the intelligent analysis module is configured to determine the stimulated condition based on the analysis results of the stimulated performance, wherein, If the stimulated performance of any two stimulated acupoints is consistent, the intelligent analysis module judges that the stimulated condition is a first stimulated condition; If the stimulated behaviors of any two stimulated acupoints are inconsistent, the intelligent analysis module judges that the stimulated condition is a second stimulated condition.
7. The artificial intelligence based acupoint stimulation system of claim 6, wherein the positioning adjustment module is configured to select a positioning adjustment based on the stimulated condition, wherein, If the stimulated condition is a first stimulated condition, the positioning adjustment module judges whether the first stimulation parameter is qualified according to the heart rate variability; if the stimulated condition is a second stimulated condition, the positioning adjustment module determines a plurality of collaborative stimulation acupoint sets according to the stimulated performance, determines local feature performance for the acupoints in each collaborative stimulation acupoint set, and determines a second output parameter according to the distribution relation of the acupoints in the collaborative stimulation acupoint sets.
8. The artificial intelligence based acupoint stimulation system of claim 7, wherein the location adjustment module is configured to determine whether the first stimulation parameter is acceptable, wherein, The positioning adjustment module compares the heart rate variability with a preset heart rate variability threshold value, and if the heart rate variability is smaller than the heart rate variability threshold value, the positioning adjustment module judges that the first stimulation parameter needs to be adjusted; if the heart rate variability is greater than or equal to the heart rate variability threshold, the positioning adjustment module determines that the first stimulation parameter does not need to be adjusted.
9. The artificial intelligence based acupoint stimulation system of claim 7, wherein the local feature performance is consistent with the stimulated performance of stimulated acupoints within the set of co-stimulated acupoints; The second output parameter is a motor output stimulation time sequence, the motor output stimulation order is consistent with the order from big to small of the area association influence distance between the collaborative stimulation acupuncture point sets, and the area association influence distance is the minimum distance between the stimulated acupuncture point in the collaborative stimulation acupuncture point set and the rest stimulated acupuncture points in the collaborative stimulation acupuncture point set.
10. The artificial intelligence based acupoint stimulation system of claim 1, wherein the muscle strain acquisition units are symmetrically distributed about the acupoint electrode.

Description

Acupuncture point stimulation system based on artificial intelligence Technical Field The invention relates to the technical field of intelligent medical treatment, in particular to an acupoint stimulation system based on artificial intelligence. Background The acupoint stimulation is used as an important application of combining the traditional Chinese medicine theory with the modern physiotherapy technology, is widely used in the scenes of health conditioning, pain relieving and the like, and the existing acupoint stimulation system mostly adopts fixed parameter output alternating current to stimulate preset acupoints, but lacks real-time perception of the contact state of the acupoints and skin, and is difficult to accurately judge whether the acupoints are stimulated effectively. Meanwhile, the existing system does not fully combine human physiological signals and muscle response characteristics to dynamically adjust stimulation parameters, and does not consider the collaborative stimulation association among a plurality of acupoints, so that the problems of insufficient stimulation pertinence, poor parameter suitability and the like often occur, the stimulation effect is uneven, and the personalized and accurate acupoint stimulation requirements cannot be met. For example, china patent publication No. CN107080894A discloses a portable multichannel acupoint stimulation system, a power supply management circuit is used for carrying out boosting and dropping management on an input power supply and providing voltage required by normal operation for the system, a mobile terminal interface is connected with the mobile terminal and is used for receiving control parameters of the mobile terminal and transmitting state information of the system to the mobile terminal, a boosting circuit is used for providing high-voltage power supply required by a bidirectional channel switch array, the bidirectional channel switch array is used for controlling on-off and polarity of multichannel stimulation signals, a current control array is used for controlling current of the multichannel stimulation signals, a controller is used for receiving the control parameters sent by the mobile terminal and generating corresponding logic signals according to the control parameters and controlling the bidirectional channel switch array and the current control array to generate required acupoint stimulation signals, and an electrode interface array is used for enabling the required acupoint stimulation signals to act on each acupoint of a human body. The following problems also exist in the prior art: The prior art lacks a dynamic parameter adjustment mechanism based on human physiological signals and muscle response characteristics, and influences the accuracy, individuation and intellectualization of acupoint stimulation. Disclosure of Invention Therefore, the invention provides an acupoint stimulation system based on artificial intelligence, which is used for solving the problems that the prior art lacks a dynamic parameter adjustment mechanism based on human physiological signals and muscle response characteristics and physiological association among different acupoints is not considered in a multi-acupoint collaborative stimulation scene. To achieve the above object, the present invention provides an artificial intelligence based acupoint stimulation system, comprising: A plurality of acupoint electrodes for outputting alternating current to stimulate acupoints; the data extraction module comprises a plurality of muscle strain acquisition units distributed around each acupoint electrode for acquiring strain values generated by the contact of the acupoint electrode with skin and a heart rate acquisition unit for acquiring heart rate signals of a human body and calculating heart rate variability; The stimulated evaluation module is respectively connected with the acupuncture point electrodes and the data extraction module and is used for controlling each acupuncture point electrode to be in a pre-output state and screening stimulated acupuncture points according to the strain value comparison condition of the muscle strain acquisition units distributed around each acupuncture point electrode in the pre-output state; The intelligent analysis module is connected with the stimulated evaluation module and used for determining the associated stimulated conditions of the stimulated acupuncture points according to the stimulated expression of the stimulated acupuncture points; The positioning adjustment module is connected with the intelligent analysis module and is used for adjusting the stimulation parameters based on the associated stimulated conditions, and comprises judging whether the first stimulation parameters are qualified or not according to heart rate variability, or determining a plurality of collaborative stimulation acupoint sets according to stimulated performance, respectively determining local characteristic performance fo