Digital instruments and their uses in music therapy

Music-based interventions using digital technology for individuals with acquired brain injuries: a scoping review

Background

The use of digital technology in music-based interventions for individuals with brain injuries has gained traction, especially post COVID-19, in addressing the need for effective, long-term rehabilitation. This scoping review examines the landscape of digital music-based interventions, focusing on their application in motor and cognitive rehabilitation for patients with brain injuries.

Methods

We conducted a literature search using five academic databases: PubMed, CINAHL, Medline, Google Scholar, and Web of Science. Twenty-six studies met the predefined criteria for inclusion in this review, and these studies were analyzed including digital interventions used.

Results

Twenty-six of 1994 studies were included. Results demonstrated a clear evolution in intervention methodologies, with earlier research focusing on rhythmic and MIDI-based tools, while more recent studies integrated virtual reality, augmented reality, and adaptive feedback mechanisms. The findings showed significant improvements in motor functions, such as upper limb movement and gait, in most of the reviewed studies, as well as some cognitive benefits, particularly when personalized music interventions were applied. However, challenges were noted regarding device complexity, cost, and inconsistent assessment methods across studies.

Discussion

Digital music-based interventions show substantial promise in enhancing motor and cognitive function for individuals with neurological impairments. Nevertheless, barriers such as technological accessibility, the need for patient comfort, and a lack of standardization in assessment remain. Future research should focus on simplifying interfaces, standardizing protocols, and exploring hybrid interventions that combine immersive virtual reality with the adaptability of music therapy to create holistic, patient-centered rehabilitation solutions.

Improve the application of reinforcement learning and multi‐modal information in music sentiment analysis

In order to improve the effect of music sentiment analysis, this paper proposes a music sentiment classification method based on lyrics and comments. This method combines lyrics and comment texts to mine richer sentiment information, and comprehensively considers the influence of the word frequency, sentiment strength and part of speech of sentiment words on sentiment classification when constructing sentiment vectors. Moreover, it matches the lyrics of the music and the substantive words in the comment with the emotional dictionary to obtain the emotional category and emotional weight of each substantive word, and calculates the statistical value of each emotional category. In addition, this paper combines reinforcement learning and multi‐modal information technology to construct a music emotion research model.

Speech recognition and artificial intelligence based on the development of music system

In the face of this increasingly intelligent society and home life, it is necessary to research and design more intelligent music systems to meet people's needs. This paper uses music speech recognition algorithms when building a music system, and combines artificial intelligence technology to apply cloud‐computing technology to the processing and transmission of music data. The system is formed by the fusion of various technologies. At the same time, using embedded technology as the core can handle multiple tasks at the same time, thereby effectively improving the efficiency of the system. In addition, based on speech recognition technology, this paper combines artificial intelligence to develop music systems. Through experimental analysis, it can be seen that the music system based on speech recognition and artificial intelligence proposed in this paper has good results.

Analysis of the value of folk music intangible cultural heritage on the regulation of mental health

This paper proposes an approach based on the safeguarding of intangible cultural heritage (ICH) by studying the value of ICH to explore the value of the ICH of folk music on mental health and its safeguarding measures. Additionally, a questionnaire survey is conducted on the value of the ICH of folk music among college students. The Tibetan Guozhuang dance and music in the ICH are taken as the object. The students' awareness, participation, and effects on physical and mental health, emotional regulation, and stress regulation are investigated, to study the safeguarding value of folk music. The survey results reveal that in the process of participating in the folk art of Tibetan Guozhuang dance, 41.8% of the students consider it very useful for emotional regulation and stress relief, and 46.31% believe it is useful. 36.95% of the students feel that it is very useful for the development of mental health, and 49.75% think it is useful. This indicates that a total of 86.7% of the students believe that the dance is helpful to the development of students' mental health. And most of the students are in a happy mood when participating in the dance. Among them, 71.7% of the students say that they are elated, and 66.98% feel that they are excited. It illustrates that as a young group, the students are fond of folk art, but they lack the cognitive approach. Finally, the safeguarding suggestions and implementation paths are put forward in view of the existing problems of the ICH of folk music. The research can provide a research reference for the safeguarding of the ICH of folk music.

Altered Functional Connectivity and Complexity in Major Depressive Disorder after Musical Stimulation

Major depressive disorder (MDD) is a common mental illness. This study used electroencephalography (EEG) to explore the effects of music therapy on brain networks in MDD patients and to elucidate changes in functional brain connectivity in subjects before and after musical stimulation. EEG signals were collected from eight MDD patients and eight healthy controls. The phase locking value was adopted to calculate the EEG correlation of different channels in different frequency bands. Correlation matrices and network topologies were studied to analyze changes in functional connectivity between brain regions. The results of the experimental analysis found that the connectivity of the delta and beta bands decreased, while the connectivity of the alpha band increased. Regarding the characteristics of the EEG functional network, the average clustering coefficient, characteristic path length and degree of each node in the delta band decreased significantly after musical stimulation, while the characteristic path length in the beta band increased significantly. Characterized by the average clustering coefficient and characteristic path length, the classification of depression and healthy controls reached 93.75% using a support vector machine.

Feature Extraction and Analysis Method of Trombone Timbre Based on CNN Model

In order to improve the accuracy of trombone timbre feature extraction, this paper combines the CNN model to construct a trombone timbre feature extraction model and summarizes the principle of trombone timbre signal. Moreover, this paper deduces the parameters of the trombone timbre signal and the corresponding network model and uses mathematical expressions to model the trombone timbre signal, which is convenient for theoretical analysis and processing of the trombone timbre signal. In addition, this paper provides a detailed discussion of time-frequency analysis techniques, including their advantages and limitations, which provide an algorithmic basis for working with trombone timbre signals. It can be seen that time-frequency analysis technology still has great advantages in trombone timbre signal processing. Finally, the simulation results show that the trombone timbre feature extraction method based on the CNN model proposed in this paper can effectively identify the trombone timbre in various musical performances.

Music Therapy in Mental Health and Emotional Diversion of Primary and Secondary School Students

The purpose of this paper is to provide a group music therapy intervention for elementary and middle school students with mood disorders through music therapy. To explore the improvement of group music therapy on the dysphoria and state of adolescent patients with mood disorders and to explore the relationship with self-identity. A music activity-based mental health education curriculum was designed based on the results of the current survey, while two homogenous classes were selected as the experimental and control classes; subsequently, the experimental teaching of the music activity-based mental health education curriculum was conducted in the experimental class, and the regular school mental health education curriculum was conducted in the control class, and the pre- and postexperimental scale tests were used to analyze that the curriculum of this study had a positive effect of this study's curriculum on elementary school students' positive emotions analyzed through pre- and postexperimental scale tests. The music activity-based mental health education program had a significant positive effect on the overall level of positive emotions of elementary school students, especially in the positive emotion index, happiness index, mental toughness, goal focus, and interpersonal assistance factor. The positive psychology-oriented music activity-based mental health education curriculum is well suited for elementary and middle school students, especially for upper elementary and middle school students. The music activity-based mental health education curriculum realizes the value of applying positive psychology to mental health education efforts at the elementary school level and flexibly uses a variety of related theories to promote positive emotional experiences for elementary and middle school students.

Inclusive Improvisation: Exploring the Line between Listening and Playing Music

The field of Accessible Digital Musical Instruments (ADMIs) is growing rapidly, with instrument designers recognising that adaptations to existing Digital Musical Instruments (DMIs) can foster inclusive music making. ADMIs offer opportunities to engage with a wider range of sounds than acoustic instruments. Furthermore, gestural ADMIs free the music maker from relying on screen, keyboard, and mouse-based interfaces for engaging with these sounds. This brings greater opportunities for exploration, improvisation, empowerment, and flow through music making for people with disability and the communities of practice they are part of. This article argues that developing ADMIs from existing DMIs can speed up the process and allow for more immediate access for those with diverse needs. It presents three case studies of a gestural DMI, originally designed by the first author for his own creative practice, played by people with disability in diverse contexts. The article shows that system-based considerations that enabled an expert percussionist to achieve virtuoso performances with the instrument required minimal hardware and software changes to facilitate greater inclusivity. Understanding the needs of players and customising the system-based movement to sound mappings was of far greater importance in making the instrument accessible.

Design and Construction of Hybrid Music Recommendation System Integrating Music Gene

In order to improve the effect of mixed music recommendation, this study combines music genes to construct a mixed music recommendation system. From the analysis of the complexity of each joint inference algorithm, GP + RKF has the highest complexity compared with the other three joint inference algorithms. Moreover, this study verifies it through the running time of the simulation experiment, using the growth method as the way of mutation. In addition, while adopting the optimal individual retention strategy, this study makes the eigenvalues of the input matrix IX all fall within the unit circle or unit circumference and makes the maximum fitness value of the individuals in the population equal to the global optimal fitness value. Finally, this study constructs an intelligent system. Through the experimental research, it can be seen that the hybrid music recommendation system based on the fusion of music genes proposed in this study has a good music recommendation effect.

Development and evaluation of a novel music-based therapeutic device for upper extremity movement training: A pre-clinical, single-arm trial

Restoration of upper limb motor function and patient functional independence are crucial treatment targets in neurological rehabilitation. Growing evidence indicates that music-based intervention is a promising therapeutic approach for the restoration of upper extremity functional abilities in neurologic conditions such as cerebral palsy, stroke, and Parkinson's Disease. In this context, music technology may be particularly useful to increase the availability and accessibility of music-based therapy and assist therapists in the implementation and assessment of targeted therapeutic goals. In the present study, we conducted a pre-clinical, single-arm trial to evaluate a novel music-based therapeutic device (SONATA) for upper limb extremity movement training. The device consists of a graphical user interface generated by a single-board computer displayed on a 32" touchscreen with built-in speakers controlled wirelessly by a computer tablet. The system includes two operational modes that allow users to play musical melodies on a virtual keyboard or draw figures/shapes whereby every action input results in controllable sensory feedback. Four motor tasks involving hand/finger movement were performed with 21 healthy individuals (13 males, aged 26.4 ± 3.5 years) to evaluate the device's operational modes and main features. The results of the functional tests suggest that the device is a reliable system to present pre-defined sequences of audiovisual stimuli and shapes and to record response and movement data. This preliminary study also suggests that the device is feasible and adequate for use with healthy individuals. These findings open new avenues for future clinical research to further investigate the feasibility and usability of the SONATA as a tool for upper extremity motor function training in neurological rehabilitation. Directions for future clinical research are discussed.

Accessible Digital Musical Instruments—A Review of Musical Interfaces in Inclusive Music Practice

Current advancements in music technology enable the creation of customized Digital Musical Instruments (DMIs). This paper presents a systematic review of Accessible Digital Musical Instruments (ADMIs) in inclusive music practice. History of research concerned with facilitating inclusion in music-making is outlined, and current state of developments and trends in the field are discussed. Although the use of music technology in music therapy contexts has attracted more attention in recent years, the topic has been relatively unexplored in Computer Music literature. This review investigates a total of 113 publications focusing on ADMIs. Based on the 83 instruments in this dataset, ten control interface types were identified: tangible controllers, touchless controllers, Brain–Computer Music Interfaces (BCMIs), adapted instruments, wearable controllers or prosthetic devices, mouth-operated controllers, audio controllers, gaze controllers, touchscreen controllers and mouse-controlled interfaces. The majority of the AMDIs were tangible or physical controllers. Although the haptic modality could potentially play an important role in musical interaction for many user groups, relatively few of the ADMIs (14.5%) incorporated vibrotactile feedback. Aspects judged to be important for successful ADMI design were instrument adaptability and customization, user participation, iterative prototyping, and interdisciplinary development teams.