Journal of Physiotherapy & Physical Rehabilitation

Objective: The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient’s exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient’s physician with recommendations for improvement. Methods: The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. Results: The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject’s performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. Conclusion: The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of machine learning and neural networks in developing a parametric model of human motions, by exploiting the representational power of these algorithms to encode nonlinear input-output dependencies over long temporal horizons.

Introduction: During the period of immobilization of mallet-fractures treated in an orthopedic way, there is sometimes a harmful secondary displacement of the distal fragment. Method: At present the splints mostly used to stabilize and immobilize the seats of these fractures, depending on opinions, are either homemade dorsal tiles or Stack splints. We have chosen to use the "custom-made" Stack’s splint. Result: The final assessment has been carried out after six months. We found no secondary displacement. The recovered mobility is excellent. The results are excellent according to the standardized criteria. Discussion: In this presentation we explain why we preferred to use, for these two mallet-fractures, a "custommade" Stack’s splint rather than a dorsal tile. The main advantage of the "custom-made" Stack is the presence of a counter surface under the Distal-Inter- Phalanx (DIP). It decreases the risk of the distal fragment of the ungueal phalanx sliding down especially if we perform, to reduce the fracture, an upward push under the distal extremity of the distal fragment. This counter surface seems to us important to counteract, throughout the treatment, against volar sliding. Conclusion: Both splints have the same function: to stabilize the extremity of the finger. Their modes of action are very similar they use holds and counter-holds to immobilize the extremity of the finger. On the other hand the "custom-made" Stack’s splint has the advantage that the dorsal tile does not have: a counter-hold placed under the seat of the fracture. For this reason we recommend using a "custom-made" Stack’s splint in spite of its drawbacks (maceration and occlusion of the pulp).

Physical activity beneficial for the skeleton. However, in the young it has been shown that also genetic predispose to a better outcome of physical training. A longitudinal study among elderly or old people coupling genotyping, physical activity and bone measures might help us to develop more specific training programs for patients in need for physiotherapy and rehabilitation programs.

Objective: To examine the effects of menstrual cycle on exercise-induced inflammation, we investigated exercise-induced changes in circulating cytokines and leukocyte responses during different phases of the menstrual cycle. Methods: Ten healthy sedentary females (20.5 ± 0.7 years) performed 60 min of cycling at 75% of their individual anaerobic threshold (AT) during the three different phases of the menstrual cycle (menstrual, follicular and luteal phases). Blood and saliva were sampled baseline, post- and 30 min post-exercise. The salivary concentrations of female sex hormones, progesterone and 17β-estradiol, and plasma concentrations of pro-inflammatory cytokines, interleukin (IL)-6 and IL-8, and markers of leukocyte activation, calprotectin and myeloperoxidase, were measured in all the blood and saliva sampling intervals. Results: The plasma concentration of IL-6 increased significantly post-exercise (p<0.001) and the plasma concentration of calprotectin increased significantly 30 min post-exercise (p<0.05) in all the three menstrual cycle phases. A positive correlation was found between exercise-induced changes in plasma IL-6 and calprotectin concentrations in the menstrual phase, suggesting the possibility of enhanced leukocyte reactivity to IL-6 during this phase. Conclusion: These findings suggest that 60 min of strenuous exercise at an intensity of higher than 75% AT may induce inflammation in sedentary females, especially during the menstrual phase of the menstrual cycle.

This short review provides an important perspective on soft tissue manipulation/mobilization (STM) as a powerful and direct form of mechanotherapy, which has significant implications in physical rehabilitation, disease prevention and health promotions. STM, e.g. therapeutic massage, whether administered by hand alone or with a rigid device, is a type of manual therapy frequently used by clinicians worldwide to address common musculoskeletal pain disorders. It is a type of mechanotherapy which applies non-invasive mechanical stimuli to the surface of the body so as to influence molecular, cell and tissue structure and function via mechanotransduction, utimately leading to improved clinical outcomes. A brief overview of mechanotransduction is provided, with a focus on the ECM-integrincytoskeleton pathway, and the impact of STM mechanical stimulus on different tissue types are considered in this article. Ongoing research is suggested to further validate STM as a viable, cost-effective treatment option in an aging population and the clinical relevance of STM is discussed. STM intervention should be approached as a prescription, a targeted and precise form of mechanotherapy in which optimal dose pressures and frequencies are delivered to achieve desired outcomes and advance the field of soft tissue manual therapies.