Nolankarstensen6205

The clinical assessment technology such as remote monitoring of rehabilitation progress for lower limb related ailments rely on the automatic evaluation of movement performed along with an estimation of joint angle information. In this paper, we introduce a transfer-learning based Long-term Recurrent Convolution Network (LRCN) named as 'MyoNet' for the classification of lower limb movements, along with the prediction of the corresponding knee joint angle. The model consists of three blocks- (i) feature extractor block, (ii) joint angle prediction block, and (iii) movement classification block. Initially, the model is end-to-end trained for knee joint angle prediction followed by transferring the knowledge of a trained model to the movement classification through transfer-learning approach making a memory and computationally efficient design. The proposed MyoNet was evaluated on publicly available University of California (UC) Irvine machine learning repository dataset of the lower limb for 11 healthy subjects and 11 subjects with knee pathology for three movements type-walking, standing with knee flexion movements and sitting with knee extension movements. The average mean absolute error (MAE) resulted in the prediction of joint angle for healthy subjects and subjects with knee pathology are 8.1 % and 9.2 % respectively. Subsequently, an average classification accuracy of 98.1 % and 92.4 % were achieved for healthy subjects and subjects with knee pathology, respectively. Interestingly, the significance of this study in itself is promising with substantial improvement in the performance compared to state-of-the-art methodologies. The clinical significance of such surface electromyography signals (sEMG) based movement recognition and prediction of corresponding joint angle system could be beneficial for remote monitoring of rehabilitation progress by the physiotherapist using wearables.Purpose of review A vasculitic pattern of injury seen on brain biopsy can be attributed to a multitude of primary or secondary disorders, leading to diagnostic challenges for clinicians. Recent findings This report describes the clinical presentation and histopathologic findings in 2 patients who initially received a diagnosis of primary CNS vasculitis, but did not show long-term response to treatment. In both cases, a second biopsy was performed, and the final diagnosis was primary CNS lymphoma (PCNSL). Summary Analyzing diagnostically challenging cases can increase recognition of PCNSL and improve outcomes in this rare condition. © 2019 American Academy of Neurology.Purpose of review Rheumatoid arthritis is a systemic inflammatory disorder, which can involve many organs; among which, CNS involvement, as in rheumatoid meningitis (RM), is rare and difficult to recognize. Our goal is to present collective data of RM cases to better characterize this disease process and to start new discussions about pathophysiology, diagnosis, and treatment. Recent findings Since Kato et al., 39 cases of RM have been reported. Approximately 59% were women, presenting with neurologic deficits (56%) and diagnosed by MRI findings, leptomeningeal enhancement (69%), after CSF analysis. Seventy-four percent were treated with corticosteroids, 64% as maintenance therapy, with 46% experiencing improvement or resolution in symptoms without relapse. Summary Diagnosis and prognosis of RM has drastically changed since the year 2000. Early detection with CSF and MRI or biopsy findings, coupled with early treatment using corticosteroids and immunologic therapy, has reduced mortality in this population. © 2019 American Academy of Neurology.Objective To explore disease burden in Parkinson disease (PD) by evaluating the prevalence of symptoms and key disease milestones (critical events, e.g., hospitalization or frequent falls) and their association with quality of life (QOL) in those with PD. Methods We created and pretested an online needs assessment survey to evaluate the clinical characteristics, QOL, symptom prevalence, and critical event frequency among those with PD. We recruited individuals with self-reported Hoehn and Yahr stage II-V PD through online postings and email through the Davis Phinney Foundation. We used logistic regression to evaluate the association between a large number of uncontrolled symptoms and events on QOL. Results A total of 612 individuals (mean age 70.1 years, 49.8% women) completed the survey. Among respondents, 13.6% reported poor QOL. XCT790 concentration Nearly 20% of respondents reported >3 falls, and 15% of respondents had been hospitalized over the previous 6 months. Participants had an average of 5.1 uncontrolled symptoms, with 86.1% of respondents reporting at least 1 uncontrolled symptom; more than 10% of respondents reported >10 uncontrolled symptoms. Depression, confusion, pain, and bothersome hallucinations were associated with poor QOL among the cohort. Conclusions In this national survey of individuals with PD, we identified poor QOL, frequent critical events, and numerous uncontrolled symptoms among a substantial proportion of respondents. Although motor symptoms were common, only nonmotor symptoms were associated with poor QOL. Many of these symptoms and events are treatable or preventable, highlighting the need for better identification and management to improve QOL among those with PD. © 2019 American Academy of Neurology.Background Quality measures (QMs) exist to operationalize guidelines by measuring adherence to guidelines through documentation, ultimately leading to improved patient outcomes. Studies are rare looking at the relationship between adherence to Parkinson disease (PD) QMs and patient outcomes. Methods We assessed adherence of our movement disorders specialists (MDSs) to the American Academy of Neurology's 2010 PD QM set through chart review using the measure set work group's criteria of documentation. We then evaluated patient outcomes to see whether there was a correlation with adherence to these QMs. Results Ninety-seven consecutive patients met the inclusion criteria. The mean disease duration was 9.3 (5.8) years. All patients were assessed by 1 of 4 MDSs. A total of 68% of QMs were documented across all patients. There was a small positive correlation between the number of documented QMs the year before the index visit and the number of calls/emails both the year before and after the index visit (r = 0.20, p = 0.