scholarly journals Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision

2015 ◽  
Vol 2 (1) ◽  
pp. e11 ◽  
Author(s):  
Cecily Morrison ◽  
Marcus D'Souza ◽  
Kit Huckvale ◽  
Jonas F Dorn ◽  
Jessica Burggraaff ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Computer Vision ◽  
Motor Dysfunction ◽  
Depth Sensing

Unraveling the neuroimaging predictors for motor dysfunction in long-standing multiple sclerosis

Neurology ◽  
2015 ◽  
Vol 85 (3) ◽  
pp. 248-255 ◽  
Author(s):  
Marita Daams ◽  
Martijn D. Steenwijk ◽  
Mike P. Wattjes ◽  
Jeroen J.G. Geurts ◽  
Bernard M.J. Uitdehaag ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Motor Dysfunction

Fixational microsaccades: A quantitative and objective measure of disability in multiple sclerosis

2020 ◽  
Vol 26 (3) ◽  
pp. 343-353 ◽  
Author(s):  
Christy K Sheehy ◽  
Ethan S Bensinger ◽  
Andrew Romeo ◽  
Lakshmisahithi Rani ◽  
Natalie Stepien-Bernabe ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Objective Measure ◽  
Motor Dysfunction ◽  
Vertical Acceleration ◽  
Eye Tracker ◽  
Logistic Regression Models ◽  
Patient Reported ◽  
Disability Status ◽  
Predictive Role ◽  
Nine Hole Peg Test

Background: Objective tools for prognosis and disease progression monitoring in multiple sclerosis (MS) are lacking. The visuomotor system could be used to track motor dysfunction at the micron scale through the monitoring of fixational microsaccades. Aims: The aim of this study was to evaluate whether microsaccades are correlated with standard MS disability metrics and to assess whether these methods play a predictive role in MS disability. Method: We used a custom-built retinal eye tracker, the tracking scanning laser ophthalmoscope (TSLO), to record fixation in 111 participants with MS and 100 unaffected controls. Results: In MS participants, a greater number of microsaccades showed significant association with higher Expanded Disability Status Scale score (EDSS, p < 0.001), nine-hole peg test (non-dominant: p = 0.006), Symbol Digit Modalities Test (SMDT, p = 0.014), and Functional Systems Scores (FSS) including brainstem ( p = 0.005), cerebellar ( p = 0.011), and pyramidal ( p = 0.009). Both brainstem FSS and patient-reported fatigue showed significant associations with microsaccade number, amplitude, and peak acceleration. Participants with MS showed a statistically different average number ( p = 0.020), peak vertical acceleration ( p = 0.003), and vertical amplitude ( p < 0.001) versus controls. Logistic regression models for MS disability were created using TSLO microsaccade metrics and paraclinical tests with ⩾80% accuracy. Conclusion: Microsaccades provide objective measurements of MS disability level and disease worsening.

Assessing Multiple Sclerosis With Kinect: Designing Computer Vision Systems for Real-World Use

2016 ◽  
Vol 31 (3-4) ◽  
pp. 191-226 ◽  
Author(s):  
Cecily Morrison ◽  
Kit Huckvale ◽  
Bob Corish ◽  
Jonas Dorn ◽  
Peter Kontschieder ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Computer Vision ◽  
Real World ◽  
Vision Systems ◽  
Computer Vision Systems

Diffusion Tensor and Magnetization Transfer Imaging Correlates of Motor Dysfunction in the Spinal Cord in Multiple Sclerosis (S21.002)

Neurology ◽  
2012 ◽  
Vol 78 (Meeting Abstracts 1) ◽  
pp. S21.002-S21.002 ◽  
Author(s):  
J. Oh ◽  
K. Zackowski ◽  
M. Chen ◽  
S. Newsome ◽  
S. Smith ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Spinal Cord ◽  
Diffusion Tensor ◽  
Magnetization Transfer ◽  
Motor Dysfunction ◽  
Magnetization Transfer Imaging

scholarly journals Automated Quantification of Macronutrients using Computer Vision on a Depth-Sensing Smartphone (Preprint)

2019 ◽  
Author(s):  
David Herzig ◽  
Christos T Nakas ◽  
Janine Stalder ◽  
Christophe Kosinski ◽  
Céline Laesser ◽  
...  
Keyword(s):  
Computer Vision ◽  
Processing Time ◽  
Energy Content ◽  
Absolute Error ◽  
Smartphone Application ◽  
Estimation Accuracy ◽  
Depth Sensor ◽  
Depth Sensing ◽  
Food Items ◽  
Macronutrient Content

BACKGROUND Quantification of dietary intake is key to the prevention and management of numerous metabolic disorders. Conventional approaches are challenging, laborious, and, suffer from lack of accuracy. The recent advent of depth-sensing smartphones in conjunction with computer vision has the potential to facilitate reliable quantification of food intake. OBJECTIVE To evaluate the accuracy of a novel smartphone application combining depth-sensing hardware with computer vision to quantify meal macronutrient content. METHODS The application ran on a smartphone with built-in depth sensor applying structured light (iPhone X) and estimated weight, macronutrient (carbohydrate, protein, fat) and energy content of 48 randomly chosen meals (type of meals: breakfast, cooked meals, snacks) encompassing 128 food items. Reference weight was generated by weighing individual food items using a precision scale. The study endpoints were fourfold: i) error of estimated meal weight; ii) error of estimated meal macronutrient content and energy content; iii) segmentation performance; and iv) processing time. RESULTS Mean±SD absolute error of the application’s estimate was 35.1±42.8g (14.0±12.2%) for weight, 5.5±5.1g (14.8±10.9%) for carbohydrate content, 2.4±5.6g (13.0±13.8%), 1.3±1.7g (12.3±12.8%) for fat content and 41.2±42.5kcal (12.7±10.8%) for energy content. While estimation accuracy was not affected by the viewing angle, the type of meal mattered with slightly worse performance for cooked meals compared to breakfast and snack. Segmentation required adjustment for 7 out of 128 items. Mean±SD processing time across all meals was 22.9±8.6s. CONCLUSIONS The present study evaluated the accuracy of a novel smartphone application with integrated depth-sensing camera and found a high accuracy in food estimation across all macronutrients. This was paralleled by a high segmentation performance and low processing time corroborating the high usability of this system.

scholarly journals PADI2-mediated citrullination is required for efficient oligodendrocyte differentiation and myelination

2018 ◽  
Author(s):  
Ana Mendanha Falcão ◽  
Mandy Meijer ◽  
Antonella Scaglione ◽  
Puneet Rinwa ◽  
Eneritz Agirre ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Corpus Callosum ◽  
Therapeutic Strategy ◽  
Chromatin Accessibility ◽  
Motor Dysfunction ◽  
Peptidylarginine Deiminase ◽  
Oligodendrocyte Differentiation ◽  
Associated Proteins ◽  
Arginine Residues ◽  
Related Proteins

Citrullination, the deimination of arginine residues into citrulline, has been implicated in the aetiology of several diseases. In multiple sclerosis (MS), citrullination is thought to be a major driver of pathology, through hypercitrullination and destabilization of myelin. As such, inhibition of citrullination has been suggested as a therapeutic strategy for MS. Here, in contrast, we show citrullination by peptidylarginine deiminase 2 (PADI2) is required for normal oligodendrocyte differentiation, myelination and motor function. We identify several targets for PADI2, including myelin-related proteins and chromatin-associated proteins, implicating PADI2 in epigenetic regulation. Accordingly, we observe that PADI2 inhibition and its knockdown affect chromatin accessibility and prevent the upregulation of oligodendrocyte differentiation genes. Moreover, mice lacking PADI2, display motor dysfunction and decreased number of myelinated axons in the corpus callosum. We conclude that citrullination is required for oligodendrocyte lineage progression and myelination and suggest its targeted activation in the oligodendrocyte lineage might be beneficial in the context of remyelination.

scholarly journals Neural Plasticity in Multiple Sclerosis: The Functional and Molecular Background

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Dominika Justyna Ksiazek-Winiarek ◽  
Piotr Szpakowski ◽  
Andrzej Glabinski
Keyword(s):  
Multiple Sclerosis ◽  
Neural Plasticity ◽  
Neuronal Plasticity ◽  
Developmental Stages ◽  
Neurodegenerative Disorder ◽  
Neuronal Damage ◽  
Brain Plasticity ◽  
Motor Dysfunction ◽  
Functional Studies ◽  
Repair Mechanisms

Multiple sclerosis is an autoimmune neurodegenerative disorder resulting in motor dysfunction and cognitive decline. The inflammatory and neurodegenerative changes seen in the brains of MS patients lead to progressive disability and increasing brain atrophy. The most common type of MS is characterized by episodes of clinical exacerbations and remissions. This suggests the presence of compensating mechanisms for accumulating damage. Apart from the widely known repair mechanisms like remyelination, another important phenomenon is neuronal plasticity. Initially, neuroplasticity was connected with the developmental stages of life; however, there is now growing evidence confirming that structural and functional reorganization occurs throughout our lifetime. Several functional studies, utilizing such techniques as fMRI, TBS, or MRS, have provided valuable data about the presence of neuronal plasticity in MS patients. CNS ability to compensate for neuronal damage is most evident in RR-MS; however it has been shown that brain plasticity is also preserved in patients with substantial brain damage. Regardless of the numerous studies, the molecular background of neuronal plasticity in MS is still not well understood. Several factors, like IL-1β, BDNF, PDGF, or CB1Rs, have been implicated in functional recovery from the acute phase of MS and are thus considered as potential therapeutic targets.

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