AffectMachine-Classical: a novel system for generating affective classical music.

This work introduces a new music generation system, called AffectMachine-Classical, that is capable of generating affective Classic music in real-time. AffectMachine was designed to be incorporated into biofeedback systems (such as brain-computer-interfaces) to help users become aware of, and ultimately mediate, their own dynamic affective states. That is, this system was developed for music-based MedTech to support real-time emotion self-regulation in users. We provide an overview of the rule-based, probabilistic system architecture, describing the main aspects of the system and how they are novel. We then present the results of a listener study that was conducted to validate the ability of the system to reliably convey target emotions to listeners. The findings indicate that AffectMachine-Classical is very effective in communicating various levels of Arousal (R2 = 0.96) to listeners, and is also quite convincing in terms of Valence (R2 = 0.90). Future work will embed AffectMachine-Classical into biofeedback systems, to leverage the efficacy of the affective music for emotional wellbeing in listeners.

Deep Cerebellar Transcranial Direct Current Stimulation of the Dentate Nucleus to Facilitate Standing Balance in Chronic Stroke Survivors-A Pilot Study.

OBJECTIVE: Cerebrovascular accidents are the second leading cause of death and the third leading cause of disability worldwide. We hypothesized that cerebellar transcranial direct current stimulation (ctDCS) of the dentate nuclei and the lower-limb representations in the cerebellum can improve functional reach during standing balance in chronic (>6 months' post-stroke) stroke survivors. MATERIALS AND METHODS: Magnetic resonance imaging (MRI) based subject-specific electric field was computed across a convenience sample of 10 male chronic (>6 months) stroke survivors and one healthy MRI template to find an optimal bipolar bilateral ctDCS montage to target dentate nuclei and lower-limb representations (lobules VII-IX). Then, in a repeated-measure crossover study on a subset of 5 stroke survivors, we compared 15minutes of 2mA ctDCS based on the effects on successful functional reach (%) during standing balance task. Three-way ANOVA investigated the factors of interest- brain regions, montages, stroke participants, and their interactions. RESULTS: "One-size-fits-all" bipolar ctDCS montage for the clinical study was found to be PO9h-PO10h for dentate nuclei and Exx7-Exx8 for lobules VII-IX with the contralesional anode. PO9h-PO10h ctDCS performed significantly (alpha = 0.05) better in facilitating successful functional reach (%) when compared to Exx7-Exx8 ctDCS. Furthermore, a linear relationship between successful functional reach (%) and electric field strength was found where PO9h-PO10h montage resulted in a significantly (alpha = 0.05) higher electric field strength when compared to Exx7-Exx8 montage for the same 2mA current. CONCLUSION: We presented a rational neuroimaging based approach to optimize deep ctDCS of the dentate nuclei and lower limb representations in the cerebellum for post-stroke balance rehabilitation. However, this promising pilot study was limited by "one-size-fits-all" bipolar ctDCS montage as well as a small sample size.

Design of Virtual Reality-Enabled Surface Electromyogram-Triggered Grip Exercise Platform.

Adequate grip ability is important for effective execution of daily living activities. Neurological disorders like stroke that result in muscle weakness, limited strength and poor control often lead to reduced grip ability in the affected limb. Conventional rehabilitation for grip training is often monotonous and subjective. Technology-assisted Virtual Reality (VR)-based rehabilitation offers a motivating environment to the participants for rehabilitation. However, the existing systems need specialized set-up architecture, thereby limiting their accessibility. Furthermore, these systems quantify the functional grip ability based on task performance, and do not explore physiological basis of grip ability. In this work, we develop a VR-based rehabilitation platform integrated with physiology-sensitive biofeedback. The developed platform, Gripx makes use of features extracted from sEMG data collected from upper limb muscles to adaptively provide audio-visual biofeedback through a VR environment. We compare task based performance, physiological indices and clinical measures to evaluate the potential of Gripx. The results of our study with 8 healthy and 12 post-stroke participants show the potential of Gripx to contribute to grip rehabilitation over multiple exposures. This approach of integrating VR-based task design with physiology-sensitive biofeedback helps patients to better assess their physiological responses and enhance the efficacy of rehabilitation.

Quantification of grip strength with complexity analysis of surface electromyogram for hemiplegic post-stroke patients.

BACKGROUND: Reduction in grip-strength due to spasticity is a common cause of impairment after stroke. OBJECTIVE: To find an objective measure of post-stroke spasticity affecting grip-strength through quantification of interaction between antagonist and agonist muscles using complexity analysis of surface electromyogrm (sEMG) signals during isometric grip in healthy and post-stroke participants. METHODS: The interaction between sEMG signals from antagonist and agonist muscles is quantified through Multiscale-Multivariate-Sample-Entropy (MMSE). This is used to quantify dissimilarity between hands of 12 healthy and 8 post-stroke participants during isometric grip. The clinical relevance of MMSE is explored by examining its correlation with spasticity score i.e. Modified-Ashworth-Scale (MAS). Further, potential of sEMG-based approach to quantify muscle-specific dissimilarity in sEMG activation across hands is investigated in terms of Cepstral-coefficients and power content of sEMG during grip tasks. RESULTS: Mean MMSE scores of sEMG signals were significantly different (p < 0.05) between paretic and non-paretic hands of Post-stroke participants. High negative correlation was observed between spasticity and complexity scores of paretic hand for post-stroke participants. CONCLUSIONS: A negative correlation between MAS and MMSE shows higher spasticity can lead to reduced complexity in sEMG. Thus, MMSE based complexity analysis can be used as an indicator of spasticity, affecting grip function.

Kinect-Assisted Performance-Sensitive Upper Limb Exercise Platform for Post-stroke Survivors.

One's ability to use upper limbs is critical for performing activities of daily living necessary for enjoying quality community life. However, after stroke, such abilities becomes adversely affected and it often deprives one of their capability to perform tasks that need coordinated movement in the upper limbs. To address issues with upper limb dysfunction, patients typically undergo rehabilitative exercises. Given the high patient to doctor ratio particularly in developing countries like India, conventional rehabilitation with patients undergoing exercises under one-on-one therapist's supervision often becomes a challenge. Thus, investigators are exploring technology such as computer-based platforms coupled with cameras that can alleviate the need for the continuous presence of a therapist and can offer a powerful complementary tool in the hands of the clinicians. Such marker-based imaging systems used for rehabilitation can offer real-time processing and high accuracy of data. However, these systems often require dedicated lab space and high set-up time. Often this is very expensive and suffers from portability issues. Investigators have been exploring marker-less imaging techniques e.g., Kinect integrated computer-based graphical user interfaces in stroke-rehabilitation such as tracking one's limb movement during rehabilitation. In our present study, we have developed a Kinect-assisted computer-based system that offered Human Computer Interaction (HCI) tasks of varying challenge levels. Execution of the tasks required one to use reaching and coordination skills of the upper limbs. Also, the system was Performance-sensitive i.e., adaptive to the individualized residual movement ability of one's upper limb quantified in terms of task performance score. We tested for the usability of our system by exposing 15 healthy participants to our system. Subsequently, seven post-stroke patients interacted with our system over a few sessions spread over 2 weeks. Also, we studied patient's mean tonic activity corresponding to the HCI tasks as a possible indicator of one's post-stroke functional recovery suggesting its potential of our system to serve as a rehabilitation platform. Our results indicate the potential of such systems toward the improvement of task performance capability of post-stroke patients with possibilities of upper limb movement rehabilitation.