Music for physical rehabilitation (1987-1996): a literature review and analysis

1998 Spring.Includes bibliographical references.A comprehensive literature review and analysis was conducted on the use of music for physical rehabilitation from 1987-1996. An earlier literature review and analysis of music for physical rehabilitation was published by Staum (1988), which covered the literature from 1950 -1986. The purpose of the current study was to provide music therapists with an updated and comprehensive resource to aid them in choosing effective treatment strategies for clients in need of physical rehabilitation. Pertinent music therapy sources, such as the Journal of Music Therapy, and pertinent non-music sources, specifically electronic bibliographic databases such as Medline, were consulted. Relevant sources were discussed in two chapters; Chapter 4 - An Overview of the Use of Music in the Treatment of Physical Rehabilitation, and Chapter 5- Clinical Implications for the Use of Music in Physical Rehabilitation . Tables containing frequency data supplement the discussion of the findings on treatment modalities, research settings, clinical population, musical applications, and literature sources. An overview of the methodology of all experimental and single-subject studies is provided in Table 8

Parkinson's Disease Classification and Clinical Score Regression via United Embedding and Sparse Learning From Longitudinal Data

Parkinson's disease (PD) is known as an irreversible neurodegenerative disease that mainly affects the patient's motor system. Early classification and regression of PD are essential to slow down this degenerative process from its onset. In this article, a novel adaptive unsupervised feature selection approach is proposed by exploiting manifold learning from longitudinal multimodal data. Classification and clinical score prediction are performed jointly to facilitate early PD diagnosis. Specifically, the proposed approach performs united embedding and sparse regression, which can determine the similarity matrices and discriminative features adaptively. Meanwhile, we constrain the similarity matrix among subjects and exploit the l2,p norm to conduct sparse adaptive control for obtaining the intrinsic information of the multimodal data structure. An effective iterative optimization algorithm is proposed to solve this problem. We perform abundant experiments on the Parkinson's Progression Markers Initiative (PPMI) data set to verify the validity of the proposed approach. The results show that our approach boosts the performance on the classification and clinical score regression of longitudinal data and surpasses the state-of-the-art approaches

One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor

Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency). Approach. Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson’s disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles. Main results. The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. Signficance. The results indicate that the neural drive in pathological tremor is compatible with one central network providing neural oscillations at the tremor frequency. Moreover, the regularity of this neural oscillation varies across tremor pathologies, making the relative amplitude of tremor harmonics a potential biomarker for diagnostic use

The computational neurology of movement under active inference

We propose a computational neurology of movement based on the convergence of theoretical neurobiology and clinical neurology. A significant development in the former is the idea that we can frame brain function as a process of (active) inference, in which the nervous system makes predictions about its sensory data. These predictions depend upon an implicit predictive (generative) model used by the brain. This means neural dynamics can be framed as generating actions to ensure sensations are consistent with these predictions-and adjusting predictions when they are not. We illustrate the significance of this formulation for clinical neurology through simulating a clinical examination of the motor system; i.e. an upper limb coordination task. Specifically, we show how tendon reflexes emerge naturally under the right kind of generative model. Through simulated perturbations, pertaining to prior probabilities of this model's variables, we illustrate the emergence of hyperreflexia and pendular reflexes, reminiscent of neurological lesions in the corticospinal tract and cerebellum. We then turn to the computational lesions causing hypokinesia and deficits of coordination. This in silico lesion-deficit analysis provides an opportunity to revisit classic neurological dichotomies (e.g. pyramidal versus extrapyramidal systems) from the perspective of modern approaches to theoretical neurobiology-and our understanding of the neurocomputational architecture of movement control based on first principles

Progress Notes

https://scholarlyworks.lvhn.org/progress_notes/1251/thumbnail.jp

Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

12 Chapters on Nuclear Medicine

The development of nuclear medicine as a medical specialty has resulted in the large-scale application of its effective imaging methods in everyday practice as a primary method of diagnosis. The introduction of positron-emitting tracers (PET) has represented another fundamental leap forward in the ability of nuclear medicine to exert a profound impact on patient management, while the ability to produce radioisotopes of different elements initiated a variety of tracer studies in biology and medicine, facilitating enhanced interactions of nuclear medicine specialists and specialists in other disciplines. At present, nuclear medicine is an essential part of diagnosis of many diseases, particularly in cardiologic, nephrologic and oncologic applications and it is well-established in its therapeutic approaches, notably in the treatment of thyroid cancers. Data from official sources of different countries confirm that more than 10-15 percent of expenditures on clinical imaging studies are spent on nuclear medicine procedures