8 results about "Music therapy" patented technology

This invention relates to a method for generating and evaluating personalized sound therapy formulas based on voice emotion recognition, belonging to the field of voice analysis, and more specifically to the field of digital music development and production. The method includes: using an AI sound therapy effect judgment model to intelligently determine the increase in the target user's happiness level after using each five-tone sound therapy formula based on the target user's current five-element attribute data and current five-organ attribute data, and the digital content of each five-tone sound therapy formula; selecting the five-tone sound therapy formula with the largest increase value as the target user's personalized sound therapy formula. This invention addresses the technical problems of difficulty in providing the most suitable personalized music therapy plan for different users and the insufficient precision of music therapy plans. It employs an AI-based traversal method to intelligently judge each sound therapy formula for the target user, and uses five-tone five-element sound therapy formulas to improve the precision of the sound therapy formulas, thereby solving the aforementioned technical problems.

The utility model discloses a music therapy equipment for psychological treatment, including equipment main part, the top one side of equipment main part is rotatedly connected with first mount frame through first pivot, one side of first mount frame is provided with first throw pillow, one side of second mount frame is provided with second throw pillow, the utility model discloses through first throw pillow, second throw pillow, when the patient sits on the equipment, can according to the demand of self and dial first mount frame, through the flexible rotation of first pivot, adjust first throw pillow to the appropriate position, simultaneously, the patient continues to dial second mount frame, utilizes the rotation function of second pivot, makes second throw pillow and first throw pillow opposite arrangement, their two hands can naturally embrace two throw pillows, can give the patient a kind of pacification and stable power, help to relieve nervous emotion, has strengthened the overall treatment effect.

This invention relates to a cognitive-emotional collaborative rehabilitation method based on brain-computer interface and AI, comprising: acquiring and preprocessing the patient's electroencephalogram (EEG) signals to obtain clean signals; inputting the clean signals into a pre-trained multimodal state assessment model, simultaneously decoding and outputting a cognitive index quantifying the cognitive state and an emotion vector representing the emotional state; generating a personalized initial music therapy plan based on the cognitive index and emotion vector using a dynamic music mapping algorithm; executing the plan, and monitoring changes in the cognitive index and emotion vector in real time during the intervention; when the changes exceed a preset threshold, dynamically adjusting at least one music parameter in the treatment plan to form a closed-loop rehabilitation intervention. This invention achieves real-time monitoring of the patient's cognitive and emotional states and adaptive adjustment of personalized music intervention, improving the accuracy and effectiveness of rehabilitation treatment.

The application relates to the technical field of data processing, and particularly discloses a postoperative index analysis method for hematopoietic stem cell transplant patients based on machine learning, which is used for solving the problem that when hematopoietic stem cell transplant patients have high-dimensional coupling of subjective scales and objective indexes at T1, T2 and T3 multiple time points, and there are missing values, batch effects and individual differences, it is difficult to realize accurate evaluation of anxiety and depression when carrying out progressive muscle relaxation training combined with music therapy, and the method comprises the following steps: collecting postoperative indexes, building a matrix and preprocessing, splitting into A and B according to columns and calculating a difference, extracting U1, U2, V1 and V2 through four-dimensional branch lifting, and obtaining U, V and X by optimization, principal component projection is carried out on X to obtain the first K dimensions and threshold pruning to obtain W, and W and group time point interaction items are input into GLMM fitting to predict anxiety and depression; through four-branch dimension lifting fusion, principal component projection and threshold pruning, compact features are formed, and GLMM is combined to model, so that the accuracy of anxiety and depression evaluation and trend prediction is improved, and the interference of data missing and batch effect is reduced.

This invention relates to the field of music therapy technology and discloses a method for evaluating the effect of music therapy based on physiological feedback. The method includes: acquiring music signals and physiological feedback signals, and constructing a physiological response sequence; performing structured analysis on the music signals to construct a music structure sequence; constructing a physiological state trajectory based on the physiological response sequence; performing music-physiological time-delay coupling analysis based on the music structure sequence and the physiological state trajectory to determine the coupling relationship; identifying the resonance interval between the music rhythm and the physiological rhythm, and performing steady-state convergence analysis; constructing a counterfactual baseline and performing offset analysis, while simultaneously performing multi-channel consistency analysis; and generating a music therapy effect evaluation result based on the above results. This invention, by establishing a time-delay correspondence between the music structure sequence and the physiological state trajectory, and by constructing a counterfactual baseline and performing offset analysis, distinguishes the physiological changes caused by music stimulation, thereby forming an evaluation method based on temporal correlation.

The application discloses a multifunctional ear moxibustion instrument, which comprises a soft rubber ear fixing body, a heat therapy unit and a music playing module. The soft rubber ear fixing body is made of medical grade silicone or thermoplastic elastomer, and is shaped to be suitable for an auricle, has good flexibility and resilience, can effectively prevent breakage during wearing and taking off, and improves the use safety and product durability. The heat therapy unit is arranged inside or on the surface of the ear fixing body, and is used for warm stimulation of ear acupoints. The music playing module is integrated inside the ear moxibustion instrument or is connected through a wired / wireless mode, and is used for playing audio required by five-element music therapy, so that a patient can receive five-element music therapy while receiving ear moxibustion treatment, and a comprehensive treatment effect of physical and mental treatment is realized. The application has a reasonable structure and convenient operation, is suitable for professional treatment of medical institutions, and is also suitable for daily health care of families, and has a significant market application prospect.

This invention discloses a music therapy response method and system that combines real-time optimization of heart rate variability (HRV), comprising: acquiring electrocardiogram signals through a wearable ECG sensor to construct a multidimensional dynamic representation vector of HRV; identifying the sensitive window for emotion regulation using sliding window covariance analysis; driving the HRV-music feature mapping network to output optimal music parameters at 100ms intervals within the window period, and generating intervention audio in real time by a hybrid synthesis engine; synchronously recording the HRV convergence slope to quantify the intervention effect and storing it in a log database; and constructing a context-response mapping map for subsequent intervention optimization by clustering intervention segments through an autoencoder. The system includes signal acquisition, feature extraction, window detection, parameter generation, audio synthesis, effect recording, and strategy optimization units. This invention achieves dynamic closed-loop control of music parameters driven by physiological signals, improving the response speed and regulation accuracy of music therapy during acute emotional fluctuations.