Background - Physiological tremor is defined as an involuntary and rhythmic shaking. Tremor of the hand is a key symptom of multiple neurological diseases, and its frequency and amplitude differs according to both dis...
Background - Physiological tremor is defined as an involuntary and rhythmic shaking. Tremor of the hand is a key symptom of multiple neurological diseases, and its frequency and amplitude differs according to both disease type and disease progression. In routine clinical practice, tremor frequency and amplitude are assessed by expert rating using a 0 to 4 integer scale. Such ratings are subjective and have poor inter-rater reliability. There is thus a clinical need for a practical and accurate method for objectively assessing hand *** - to develop a proof-of-principle method to measure hand tremor amplitude from smartphone *** - We created a computer vision pipeline that automatically extracts salient points on the hand and produces a 1-D time series of movement due to tremor, in pixels. Using the smartphones’ depth measurement, we convert this measure into real distance units. We assessed the accuracy of the method using 60 videos of simulated tremor of different amplitudes from two healthy adults. Videos were taken at distances of 50, 75 and 100 cm between hand and camera. The participants had skin tone II and VI on the Fitzpatrick scale. We compared our method to a gold-standard measurement from a slide rule. Bland-Altman methods agreement analysis indicated a bias of 0.04 cm and 95% limits of agreement from -1.27 to 1.20 cm. Furthermore, we qualitatively observed that the method was robust to limited *** relevance - We have demonstrated how tremor amplitude can be measured from smartphone videos. In conjunction with tremor frequency, this approach could be used to help diagnose and monitor neurological diseases.
This paper introduces the design of a USB interface temperature and humidity detector. System firmware is implemented by RTL logic based on CPLD, such as interface timing, data processing, communication and so on. USB...
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Many students find anatomy concepts overwhelming and difficult to grasp, therefore, understanding how anatomy is learned, and the influences thereon is important to ensure academic performance. To evaluate student div...
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.Abstracting eye models from MRI images is critical in advancing medical imaging, particularly for clinical diagnostics. Current methods often struggle with accuracy and efficiency, highlighting a gap this research ai...
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.Abstracting eye models from MRI images is critical in advancing medical imaging, particularly for clinical diagnostics. Current methods often struggle with accuracy and efficiency, highlighting a gap this research aims to fill. This study investigates the application of machine learning methods, focusing on the U-net-based deep learning framework, to improve the accuracy of eye model extraction. The objectives include fitting measured eye data to models such as the Ellipsoid model, evaluating automated segmentation tools, and assessing the usability of machine learning-based extractions in clinical scenarios. We employed point cloud data of 202,872 points to fit eye models using ellipsoid, non-linear, and spherical fitting techniques. The fitting processes were optimized to ensure precision and reliability. We compared the performance of these models using mean squared error (MSE) as the primary metric. The non-linear model emerged as the most accurate, with a significantly lower MSE (1.186562) compared to the ellipsoid (781.0542) and spherical models. This finding indicates that the non-linear model provides a more detailed and precise representation of the eye’s geometry. These results suggest that machine learning methods, particularly non-linear models, can significantly enhance the accuracy and usability of eye model extraction in clinical diagnostics, offering a robust framework for future advancements in medical imaging.
Arabic is the world’s first language,categorized by its rich and complicated grammatical ***,the Arabic morphology can be perplexing because nearly 10,000 roots and 900 patterns were the basis for verbs and *** Arabi...
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Arabic is the world’s first language,categorized by its rich and complicated grammatical ***,the Arabic morphology can be perplexing because nearly 10,000 roots and 900 patterns were the basis for verbs and *** Arabic language consists of distinct variations utilized in a community and particular *** media sites are a medium for expressing opinions and social phenomena like racism,hatred,offensive language,and all kinds of verbal *** conduct does not impact particular nations,communities,or groups only,extending beyond such areas into people’s everyday *** study introduces an Improved Ant Lion Optimizer with Deep Learning Dirven Offensive and Hate Speech Detection(IALODL-OHSD)on Arabic *** presented IALODL-OHSD model mainly aims to detect and classify offensive/hate speech expressed on social *** the IALODL-OHSD model,a threestage process is performed,namely pre-processing,word embedding,and ***,data pre-processing is performed to transform the Arabic social media text into a useful *** addition,the word2vec word embedding process is utilized to produce word *** attentionbased cascaded long short-term memory(ACLSTM)model is utilized for the classification ***,the IALO algorithm is exploited as a hyperparameter optimizer to boost classifier *** illustrate a brief result analysis of the IALODL-OHSD model,a detailed set of simulations were *** extensive comparison study portrayed the enhanced performance of the IALODL-OHSD model over other approaches.
Navigation safety of both sea-going crewed ships and sea-going autonomous unmanned ships is possible to improve by enhancing navigation engineering facilities, including software and soft hardware (firmware), providin...
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We investigate a model, inspired by Johnson et al. (2017), see [8], to describe the movement of a biological population which consists of isolated and grouped organisms. We introduce biases in the movements and then o...
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Methodological and algorithmic bases of the local-regional and global wireless networks operation for functional states of people long-term monitoring, processing, encoding, encrypting and transmitting samples of moni...
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Motivation: The size of available omics datasets is steadily increasing with technological advancement in recent years. While this increase in sample size can be used to improve the performance of relevant prediction ...
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In recent years, Deep Learning has gained popularity for its ability to solve complex classification tasks, increasingly delivering better results thanks to the development of more accurate models, the availability of...
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