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This study developed a method of discriminating real-time motion from electromyogram (EMG) signals. We previously proposed a real-time motion discrimination method using hyper-sphere models that discriminated five motions (open, grasp, pinching, wrist extension, and wrist flexion) above 90% and quickly learned EMG signals. Our method prevents elbow motions from interfering with hand motion discrimination...
Pianists who practice hours per day may have a risk for developing playing-related musculoskeletal injuries if they do not play with proper hand alignment. In order to detect the harmful, misaligned hand postures (such as wrist flexion and extension, knuckle collapse, and ulnar and radial deviation) and analyze the injury risk, a motion capture system was developed using the Microsoft Kinect depth...
Behavior tracking with severely disabled children can be a challenge, since dealing directly with a child's behavior is more immediately pressing than the need to record an event for tracking purposes. By the time a paraeducator (‘para’) is able to break away and record events, behavior counts can be forgotten. This paper presents a paraeducator glove design that can help to track behaviors with minimal...
Biological imaging of live cell and tissue using 3D microscopy is able to capture time-lapse image sequences showing multiple molecular markers labeling different biological structures simultaneously. In order to analyze this complex multi-dimensional image sequence data, there is a need for automated quantitative algorithms, and for methods to visualize and interact with both the data and the analytical...
Individual finger movements are well-articulated movements of fine body parts, the successful decoding of which can provide extra degrees of freedom to drive brain computer interface (BCI) applications. Past studies present some unique features revealed from spectral principal component analysis (PCA) on electrophysiological data recorded in both the surface of the brain (electrocorticography, ECoG)...
Pulse Transit Time (PTT) is the time it takes for an arterial pulsation to travel from the heart to a peripheral site. In recent times, PTT has been advocated as a marker for assessing increased vascular resistance. However, the reliability of PTT as a marker for cardiovascular risks and its inverse relation to beat-to-beat blood pressure is still being investigated. In order to validate the technique...
A recently developed and evaluated upper extremity (UE) markerless motion analysis system based on the Microsoft® Kinect® has potential for improving functional assessment of patients with hemiplegic cerebral palsy. 12 typically-developing adolescents ages 12–17 were evaluated using both the Kinect-based system and the Shriners Hospitals for Children Upper Extremity Evaluation (SHUEE), a validated...
In this paper we present a series of design directions for the development of affordable, compliant, modular, underactuated robot fingers, that can be used as prostheses by amputees that suffer from various partial hand amputations (index to pinky fingers are considered). Our design is based on parametric models that have been derived from hand anthropometry studies. Various interfaces have been considered...
Most of the currently available prosthetic hands do not have a proper sensation of touching and slipping. Thus it is not easy for arm amputees to grasp objects properly only with an assistance of visual feedback. In this pilot work, a sensor based on thin-film piezoelectret was used to detect the possible tactile and slip information of a prosthetic hand. The piezoelectret sensor is flexible and is...
Brain computer interface (BCI) control predominately uses visual feedback. Real arm movements, however, are controlled under a diversity of feedback mechanisms. The lack of additional BCI feedback modalities forces users to maintain visual contact while performing tasks. Such stringent requirements result in poor BCI control during tasks that inherently lack visual feedback, such as grasping, or when...
Rehabilitation of arm and hand function is crucial to increase functional independence of stroke subjects. Here, we investigate the technical feasibility of an integrated training system combining robotics and functional electrical stimulation (FES) to support reach and grasp during functional manipulation of objects. To support grasp and release, FES controlled the thumb and fingers using Model Predictive...
Automated motor unit (MU) decomposition algorithms of surface electromyogram (EMG) have been developed recently. However, a routine estimate of the decomposition accuracy is still lacking. The objective of this preliminary study was to examine the statistics of the inter-spike intervals (ISIs) of the identified MUs as a measure of the decomposition accuracy, such that the ISI analysis can be used...
Timed measures of standardized functional tasks are commonly used to measure treatment effects in persons with upper extremity (UE) paresis due to stroke. The effectiveness of their ability to measure motor recovery has come into question because of their inability to distinguish between motor recovery and compensations. This paper presents three linear regression models generated from twelve kinematic...
Many hand exoskeleton devices have recently been developed for hand rehabilitation of stroke survivors, but most hand exoskeletons focused on implementing joint movement driven by individual actuator located at the finger joints rather than considering function of hand muscle-tendons and their coordination. In order to achieve hand rehabilitation targeted on restoration of specific muscle-tendon functions,...
This paper reports the classification of finger flexion and extension of surface Electromyography (EMG) and Cyberglove data using the modified Independent Component Analysis (ICA) weight matrix. The finger flexion and extension data are processed through Principal Component Analysis (PCA), and next separated using modified ICA for each individual with customized weight matrix. The extension and flexion...
Current brain-machine interfaces (BMIs) allow upper limb amputees to position robotic arms with a high degree of accuracy, but lack the ability to control hand pre-shaping for grasping different objects. We have previously shown that low frequency (0.1–1 Hz) time domain cortical activity recorded at the scalp via electroencephalography (EEG) encodes information about grasp pre-shaping. To transfer...
Wrist-worn accelerometers are becoming more prevalent as a means to assess use of the impaired upper extremity in daily life after stroke. However, wrist accelerometry does not measure joint movements of the hand, which are integral to functional use of the upper extremity. In this study, we used a custom-built, non-obtrusive device called the manumeter to measure both arm use (via wrist accelerometry)...
The use of a small number of surface electromyography (EMG) channels on the transradial amputee in a myoelectric controller is a big challenge. This paper proposes a pattern recognition system using an extreme learning machine (ELM) optimized by particle swarm optimization (PSO). PSO is mutated by wavelet function to avoid trapped in a local minima. The proposed system is used to classify eleven imagined...
Human hands are the most dexterous of human limbs and hand gestures play an important role in non-verbal communication. Underlying electromyograms associated with hand gestures provide a wealth of information based on which varying hand gestures can be recognized. This paper develops an inter-individual hand gesture recognition model based on Hidden Markov models that receives surface electromyography...
Joint incongruity is often cited as a possible etiological factor for the high incidence of thumb carpometacarpal (CMC) joint osteoarthritis (OA) in older women. There is evidence suggesting that biomechanics plays a role in CMC OA progression, but little is known about how CMC joint congruence, specifically, differs among different cohorts. The purpose of this in vivo study was to determine if CMC...
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