Metabolic Cost and Mechanical Efficiency of a Novel Handle-Based Device for Wheelchair Propulsion.

OBJECTIVE: To investigate differences in metabolic cost and gross mechanical efficiency of a novel handlebased wheelchair propulsion device and to compare its performance with conventional push-rim propulsion. DESIGN: Double-group comparative study between 2 different propulsion methods. PARTICIPANTS: Eight paraplegic individuals and 10 non-disabled persons. METHODS: Participants performed the same exercise using a push-rim device and the novel handle-based device on a wheelchair- based test rig. The exercise consisted of a combined submaximal and maximal test. Power output, oxygen uptake, ventilation, respiratory exchange ratio and heart rate were recorded continuously during the tests. Analysis of variance was performed to determine the effects of group, mode and on power output. RESULTS: Submaximal exercise resulted in a higher efficiency for the novel device and significant main effects of propulsion mode on all investigated parameters, except heart rate. On the respiratory exchange ratio, a significant interaction effect was found for both mode and group. The maximal exercise resulted in a higher peak power output and lower peak heart rate during propulsion using the handle-based device. A significant main effect on mode for mean peak power output, ventilation and heart rate was also observed. CONCLUSION: Wheelchair propulsion using the handle-based device resulted in lower physical responses and higher mechanical efficiency, suggesting that this novel design may be well suited for indoor use, thereby offering an attractive alternative to pushrim wheelchairs.

Ivermectin treatment in rosacea: How novel smartphone technology can support monitoring rosacea-associated signs and symptoms.

Rosacea lessens patients' quality of life not only by visible symptoms like erythema, papules, and pustules but also by invisible symptoms like stinging, burning, and dryness. Ivermectin 1% cream has recently been introduced as an efficient therapy for papules and pustules in rosacea patients. To investigate the potential of ivermectin 1% cream to improve rosacea-associated erythema and invisible symptoms by combining established questionnaires with the novel photography and analysis tool Scarletred®Vision. We performed an open monocentric pilot study including 25 Caucasian patients presenting with moderate to severe rosacea with erythema, less than 10 papules and/or pustules, and ≥ 15 Demodex mites/cm2 . Patients applied 1 g of ivermectin 1% cream (Soolantra®) once a day for ≥16 weeks. Skin symptoms were recorded at baseline, week 8 and ≥ week 16. Grade of erythema was determined by clinician erythema assessment (CEA) and patient self-assessment (PSA). Severity of invisible skin symptoms (stinging and/or burning, dryness, itching) were assessed by questionnaire. Erythema and skin texture were additionally quantified using Scarletred®Vision. Ivermectin 1% cream significantly reduced invisible symptoms of rosacea (stinging and/or burning, dryness: p < 0.0001; itching p < 0.001; at ≥16 weeks). Analysis with Scarletred®Vision confirmed CEA and PSA results for improvement of erythema (p < 0.0001; at ≥16 weeks) and skin roughness (p < 0.001; at ≥16 weeks). Treatment with ivermectin 1% cream is efficient in treating not only rosacea-associated papules and pustules but also erythema and invisible skin symptoms.

The mathematics of erythema: Development of machine learning models for artificial intelligence assisted measurement and severity scoring of radiation induced dermatitis.

Although significant advancements in computer-aided diagnostics using artificial intelligence (AI) have been made, to date, no viable method for radiation-induced skin reaction (RISR) analysis and classification is available. The objective of this single-center study was to develop machine learning and deep learning approaches using deep convolutional neural networks (CNNs) for automatic classification of RISRs according to the Common Terminology Criteria for Adverse Events (CTCAE) grading system. ScarletredⓇ Vision, a novel and state-of-the-art digital skin imaging method capable of remote monitoring and objective assessment of acute RISRs was used to convert 2D digital skin images using the CIELAB color space and conduct SEV* measurements. A set of different machine learning and deep convolutional neural network-based algorithms has been explored for the automatic classification of RISRs. A total of 2263 distinct images from 209 patients were analyzed for training and testing the machine learning and CNN algorithms. For a 2-class problem of healthy skin (grade 0) versus erythema (grade ≥ 1), all machine learning models produced an accuracy of above 70%, and the sensitivity and specificity of erythema recognition were 67-72% and 72-83%, respectively. The CNN produced a test accuracy of 74%, sensitivity of 66%, and specificity of 83% for predicting healthy and erythema cases. For the severity grade prediction of a 3-class problem (grade 0 versus 1 versus 2), the overall test accuracy was 60-67%, and the sensitivities were 56-82%, 35-59%, and 65-72%, respectively. For estimating the severity grade of each class, the CNN obtained an accuracy of 73%, 66%, and 82%, respectively. Ensemble learning combines several individual predictions to obtain a better generalization performance. Furthermore, we exploited ensemble learning by deploying a CNN model as a meta-learner. The ensemble CNN based on bagging and majority voting shows an accuracy, sensitivity and specificity of 87%, 90%, and 82% for a 2-class problem, respectively. For a 3-class problem, the ensemble CNN shows an overall accuracy of 66%, while for each grade (0, 1, and 2) accuracies were 76%, 69%, and 87%, sensitivities were 70%, 57%, and 71%, and specificities were 78%, 75%, and 95%, respectively. This study is the first to focus on erythema in radiation-dermatitis and produces benchmark results using machine learning models. The outcome of this study validates that the proposed system can act as a pre-screening and decision support tool for oncologists or patients to provide fast, reliable, and efficient assessment of erythema grading.

A preliminary muscle activity analysis: Handle based and push-rim wheelchair propulsion.

Approximately ninety percent of the wheelchair users worldwide prefer the conventional push rim mode of propulsion for daily mobility and rehabilitation. Even though push-rim wheelchairs help to promote a healthy life style, the high muscular demand and the non-continuous push motions can lead to serious upper extremity injuries. In this study, muscle EMG data of ten healthy subjects were recorded for a newly introduced handle based propulsion mechanism (HBP) and compared to conventional push-rim propulsion at two workloads, 25 W and 35 W respectively. The results for the mean peak muscle activations at both workloads demonstrate that push-rim propulsion leads to higher peak muscle activity compared to HBP at a similar wheelchair forward velocity of 1.11 m/s. The generation of these high peak muscle activations with increasing loads in push-rim propulsion over time can lead to overuse injuries. Overall, the use of the HBP mechanism is less straining to the muscles and may reduce fatigue during prolonged propulsion.

Forward dynamic optimization of handle path and muscle activity for handle based isokinetic wheelchair propulsion: A simulation study.

Push-rim wheelchair propulsion is biomechanically inefficient and physiologically stressful to the musculoskeletal structure of human body. This study focuses to obtain a new, optimized propulsion shape for wheelchair users, which is within the ergonomic ranges of joint motion, thus reducing the probability of injuries. To identify the propulsion movement, forward dynamic optimization was performed on a 3D human musculoskeletal model linked to a handle based propulsion mechanism, having shape and muscle excitations as optimization variables. The optimization resulted in a handle path shape with a circularity ratio of 0.95, and produced a net propulsion power of 34.7 watts for an isokinetic propulsion cycle at 50 rpm. Compared to push-rim propulsion, the compact design of the new propulsion mechanism along with the ergonomically optimized propulsion shape may help to reduce the risk of injuries and thus improve the quality of life for wheelchair users.

Wrist Kinematics and Kinetics during Wheelchair Propulsion with a Novel Handle-based Propulsion Mechanism.

Wheelchairs are important for daily mobility and recreation of the elderly and physically challenged individuals. The non-ergonomical propulsion design of wheelchairs frequently causes injuries to the upper extremities, especially in the wrist region. In this study, the joint kinematics and kinetics of the wrist joint was analyzed on subjects propelling a novel handle based wheelchair propulsion unit at 1.2m/s speed (20W and 40W respectively). The joint kinematics and the joint moments of the wrist were determined using a 3D musculoskeletal model. The mean values of joint ranges and torques during propulsion at the mentioned speeds were lower when compared to standard wheelchair propulsion with the push-rim, making the novel propulsion mechanism with its compact design an interesting alternative for wheelchair users that might help to avoid or reduce joint injuries.