IEEE Transactions on Biomedical Engineering

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Stable Responsive EMG Sequence Prediction and Adaptive Reinforcement with Temporal Convolutional Networks
Movement prediction from EMG can be performed by compressing a short window of EMG into a feature-encoding that is meaningful for classification— an approach that can cause erratic prediction behavior. Temporal convolutional networks (TCN) leverage temporal information from EMG to achieve superior predictions for 3 simultaneous degrees-of-freedom that are more accurate and stable, have a very low response delay, and allow for novel types of interactive training. Addressing EMG decoding as a sequential prediction problem requires a new set of considerations that will lead to enhancements in the reliability, responsiveness, and movement complexity available from prosthesis control systems... Read more
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Bilevel Optimization for Cost Function Determination in Dynamic Simulation of Human Gait
      Predictive simulation based on dynamic optimization using musculoskeletal models is a powerful approach for studying human gait. Predictive musculoskeletal simulation may be used for a variety of applications from designing assistive devices to testing theories of motor control. However, the... Read more
Articles, Published Articles
Reduced Rank Least Squares for Real-Time Short Term Estimation of Mean Arterial Blood Pressure in Septic Patients Receiving Norepinephrine
    Abstract Norepinephrine (NE), an endogenous catecholamine, is a mainstay treatment for septic shock, which is a life-threatening manifestation of severe infection. NE counteracts the loss in blood pressure associated with septic shock. However, an NE infusion that is too low fails... Read more
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MfeCNN: Mixture Feature Embedding Convolutional Neural Network for Data Mapping
Data mapping plays an important role in data integration and exchanges among institutions and organizations with different data standards. However, traditional rule-based approaches and machine learning methods fail to achieve satisfactory results for the data mapping problem. In this paper,... Read more
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A Model to Estimate the Optimal Layout for Assistive Communication Touchscreen Devices in Children With Dyskinetic Cerebral Palsy
  Excess involuntary movements and slowness of movement in children with dyskinetic cerebral palsy often result in the inability to properly interact with augmentative and alternative communication (AAC) devices. This significantly limits communication. It is, therefore, essential to know how to... Read more
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Screening for Cognitive Impairment by Model Assisted Cerebral Blood Flow Estimation
Alzheimer’s disease is a progressive and debilitating neurodegenerative disease; one in ten people aged 65 and older have it. As there is no cure for Alzheimer’s disease, early diagnosis is crucial so that mitigating treatments can be initiated as soon... Read more
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TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine
As one of the most ubiquitous post-transcriptional modifications of RNA, N6-methyladenosine ( m 6 A  ) plays an essential role in many vital biological processes. The identification of m 6 A  sites in RNAs is significantly important for both basic biomedical research and practical... Read more