Gait control of migraine patients with increasing light and sound levels.

BACKGROUND: Under a typical light and sound environment context, individuals with migraine showed balance control deficits on a series of functional activities, which helps to explain why migraineurs report more falls. it isn't established, the effects of intensity light and sound in migraineurs during functional tasks. RESEARCH QUESTION: Based on the hypersensitivity to light and sound in migraineurs, not only during the attack but also in the interictal period, does the exposure to bright light and loud sound impact motor control in this population? METHODS: This cross-sectional study consisted of 51 women with migraine and 22 healthy women. They performed three walking tasks: crossing an obstacle, stepping-up and stepping-down a curb, in a control situation with ambient lighting (≅350 lux), bright light (≅1200 lux), and loud sound (≅90 dBa). For statistical analysis, a t-test, a Spearman correlation test, and a repeated measures mixed ANOVA were applied. RESULTS: Migraineurs presented higher discomfort induced by light (p ≤ 0.0001) and sound (p = 0.001). In the obstacle task, migraineurs had greater step width than controls in the ambient light condition (p = 0.038) and participants of both groups placed their leading foot farther away from the obstacle in the light (p = 0.033) than in the ambient light condition. For the step-up task, this distance increased for both groups and limbs in the light (leading limb: p = 0.015; trailing limb: p = 0.002) and sound (leading limb: p = 0.010; trailing limb: p ≤ 0.0001) conditions compared to the ambient light condition. Step speed increased for light and sound conditions compared to ambient light condition, except for the sound condition in the step-down task. SIGNIFICANCE: Despite the higher discomfort induced by light and sound in the migraineurs, the effects of these sensory manipulations were similar for both migraineurs and controls, except for step width. Light and sound manipulation induced a less conservative strategy to deal with uneven terrain in both groups.

Brazilian Portuguese version of the Headache Disability Inventory: Cross-cultural adaptation, validity, and reliability.

BACKGROUND: The Headache Disability Inventory assesses the dimensions of headache disability, but it is not available in Brazilian Portuguese yet. We aimed to translate the Headache Disability Inventory into Brazilian Portuguese and analyze its measurement properties. METHODS: Consecutive patients with headaches diagnosed by expert neurologists as per the International Classification of Headache Disorders were included. For the cross-cultural adaptation, 30 individuals answered the translated Headache Disability Inventory version. The internal consistency was evaluated, and the structural validity was assessed through exploratory factor analysis. For the construct validity assessment, 132 individuals answered the Headache Disability Inventory-Brazil, 12-item Short Form Survey (SF-12), and Headache Impact Test (HIT-6). After 1-3 weeks, 67 individuals again answered the Headache Disability Inventory-Brazil for the reliability assessment. The Pearson's correlation test, the intraclass correlation coefficient and the standard error of measurement were analyzed. RESULTS: The pre-stage version of the questionnaire was considered as the final version. The Headache Disability Inventory-Brazil had an internal consistency of 0.84 and consisted of a functional, emotional and social participation domain (factor loads > 0.3). The internal consistency ranged from 0.81 to 0.93 for each of the three domains. For the construct validity, the Headache Disability Inventory-Brazil presented moderate correlation with the SF-12 (r = -0.70, p < 0.05) and with the HIT-6 (r = 0.67, p ≤ 0.05). Its test-retest reliability was considered to be excellent (intraclass correlation coefficient = 0.95) and the standard error of measurement was 2.26 points. CONCLUSION: The Headache Disability Inventory-Brazil was successfully translated and culturally adapted to the Brazilian population. It can be used for the impact assessment of primary and secondary headaches with validity and reliability equivalent to its original version.

Can physical testing be used to distinguish between migraine and cervicogenic headache sufferers? A protocol for a systematic review.

INTRODUCTION: Differential diagnosis of migraine and cervicogenic headache (CGH) can be challenging given the large overlap of symptoms, commonly leading to misdiagnosis and ineffective treatment. In order to strengthen the differential diagnosis of headache, previous studies have evaluated the utility of physical tests to examine for musculoskeletal impairment, mainly in the cervical spine, which could be provoking or triggering headache. However, no systematic review has attempted to evaluate whether physical tests can differentiate CGH from migraine or both conditions from asymptomatic subjects. METHODS/ANALYSIS: A systematic review protocol has been designed and is reported in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). A sensitive topic-based search strategy is planned which will include databases, hand searching of key journals and consultation of relevant leading authors in this field. Terms and keywords will be selected after discussion and agreement. Two independent reviewers will perform the search and select studies according to inclusion and exclusion criteria, including any cohort or observational studies evaluating the topic of this review; a third reviewer will confirm accuracy. A narrative synthesis will be developed for all included studies and, if possible, a meta-analysis will be conducted. The overall quality of the evidence will be assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklist for diagnostic accuracy studies and the Downs and Black scale for those studies where the QUADAS-2 checklist cannot be applied. ETHICS AND DISSEMINATION: Ethical approval is not required since no patient information will be collected. The results will provide a deeper understanding about the possibility of using physical tests to differentiate cervicogenic headache from migraine and from asymptomatic subjects, which has direct relevance for clinicians managing people with headache. The results will be published in a peer-reviewed journal and presented at scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42019135269.

Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment.

The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech and image classification, but it has not been fully investigated as a potential approach to analyze wearable sensor data. We collected data from ten patients with idiopathic Parkinson's disease using inertial measurement units. Several motor tasks were expert-labeled and used for classification. We specifically focused on the detection of bradykinesia. For this, we compared standard machine learning pipelines with deep learning based on convolutional neural networks. Our results showed that deep learning outperformed other state-of-the-art machine learning algorithms by at least 4.6 % in terms of classification rate. We contribute a discussion of the advantages and disadvantages of deep learning for sensor-based movement assessment and conclude that deep learning is a promising method for this field.