Matching Items (5)

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Smart glove: an assistive device to enhance recovery of hand function during motor rehabilitation

Description

Stroke accounts for high rates of mortality and disability in the United States. It levies great economic burden on the affected subjects, their family and the society at large. Motor

Stroke accounts for high rates of mortality and disability in the United States. It levies great economic burden on the affected subjects, their family and the society at large. Motor impairments after stroke mainly manifest themselves as hemiplegia or hemiparesis in the upper and lower limbs. Motor recovery is highly variable but can be enhanced through motor rehabilitation with sufficient movement repetition and intensity. Cost effective assistive devices that can augment therapy by increasing movement repetition both at home and in the clinic may facilitate recovery. This thesis aims to develop a Smart Glove that can enhance motor recovery by providing feedback to both the therapist and the patient on the number of hand movements (wrist and finger extensions) performed during therapy. The design implements resistive flex sensors for detecting the extensions and processes the information using the Lightblue bean microcontroller mounted on the wrist. Communication between the processing unit and display module is wireless and executes Bluetooth 4.0 communication protocol. The capacity for the glove to measure and record hand movements was tested on three stroke and one traumatic brain injured patient while performing a box and blocks test. During testing many design flaws were noted and several were adapted during testing to improve the function of the glove. Results of the testing showed that the glove could detect wrist and finger extensions but that the sensitivity had to be calibrated for each patient. It also allowed both the therapist and patient to know whether the patient was actually performing the task in the manner requested by the therapist. Further work will reveal whether this feedback can enhance recovery of hand function in neurologically impaired patients.

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Agent

Created

Date Created
  • 2015

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A musculoskeletal model of the human hand to improve human-device interaction

Description

Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly

Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.

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Agent

Created

Date Created
  • 2014

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Sensory-motor integration for control of digit position in grasping and manipulation

Description

Dexterous manipulation is a representative task that involves sensorimotor integration underlying a fine control of movements. Over the past 30 years, research has provided significant insight, including the control mechanisms

Dexterous manipulation is a representative task that involves sensorimotor integration underlying a fine control of movements. Over the past 30 years, research has provided significant insight, including the control mechanisms of force coordination during manipulation tasks. Successful dexterous manipulation is thought to rely on the ability to integrate the sense of digit position with motor commands responsible for generating digit forces and placement. However, the mechanisms underlying the phenomenon of digit position-force coordination are not well understood. This dissertation addresses this question through three experiments that are based on psychophysics and object lifting tasks. It was found in psychophysics tasks that sensed relative digit position was accurately reproduced when sensorimotor transformations occurred with larger vertical fingertip separations, within the same hand, and at the same hand posture. The results from a follow-up experiment conducted in the same digit position-matching task while generating forces in different directions reveal a biased relative digit position toward the direction of force production. Specifically, subjects reproduced the thumb CoP higher than the index finger CoP when vertical digit forces were directed upward and downward, respectively, and vice versa. It was also found in lifting tasks that the ability to discriminate the relative digit position prior to lifting an object and modulate digit forces to minimize object roll as a function of digit position are robust regardless of whether motor commands for positioning the digits on the object are involved. These results indicate that the erroneous sensorimotor transformations of relative digit position reported here must be compensated during dexterous manipulation by other mechanisms, e.g., visual feedback of fingertip position. Furthermore, predicted sensory consequences derived from the efference copy of voluntary motor commands to generate vertical digit forces may override haptic sensory feedback for the estimation of relative digit position. Lastly, the sensorimotor transformations from haptic feedback to digit force modulation to position appear to be facilitated by motor commands for active digit placement in manipulation.

Contributors

Agent

Created

Date Created
  • 2014

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Cortical sensorimotor mechanisms for neural control of skilled manipulation

Description

The human hand is a complex biological system. Humans have evolved a unique ability to use the hand for a wide range of tasks, including activities of daily living such

The human hand is a complex biological system. Humans have evolved a unique ability to use the hand for a wide range of tasks, including activities of daily living such as successfully grasping and manipulating objects, i.e., lifting a cup of coffee without spilling. Despite the ubiquitous nature of hand use in everyday activities involving object manipulations, there is currently an incomplete understanding of the cortical sensorimotor mechanisms underlying this important behavior. One critical aspect of natural object grasping is the coordination of where the fingers make contact with an object and how much force is applied following contact. Such force-to-position modulation is critical for successful manipulation. However, the neural mechanisms underlying these motor processes remain less understood, as previous experiments have utilized protocols with fixed contact points which likely rely on different neural mechanisms from those involved in grasping at unconstrained contacts. To address this gap in the motor neuroscience field, transcranial magnetic stimulation (TMS) and electroencephalography (EEG) were used to investigate the role of primary motor cortex (M1), as well as other important cortical regions in the grasping network, during the planning and execution of object grasping and manipulation. The results of virtual lesions induced by TMS and EEG revealed grasp context-specific cortical mechanisms underlying digit force-to-position coordination, as well as the spatial and temporal dynamics of cortical activity during planning and execution. Together, the present findings provide the foundation for a novel framework accounting for how the central nervous system controls dexterous manipulation. This new knowledge can potentially benefit research in neuroprosthetics and improve the efficacy of neurorehabilitation techniques for patients affected by sensorimotor impairments.

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Agent

Created

Date Created
  • 2017

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Neural mechanisms of sensory integration: frequency domain analysis of spike and field potential activity during arm position maintenance with and without visual feedback

Description

Understanding where our bodies are in space is imperative for motor control, particularly for actions such as goal-directed reaching. Multisensory integration is crucial for reducing uncertainty in arm position

Understanding where our bodies are in space is imperative for motor control, particularly for actions such as goal-directed reaching. Multisensory integration is crucial for reducing uncertainty in arm position estimates. This dissertation examines time and frequency-domain correlates of visual-proprioceptive integration during an arm-position maintenance task. Neural recordings were obtained from two different cortical areas as non-human primates performed a center-out reaching task in a virtual reality environment. Following a reach, animals maintained the end-point position of their arm under unimodal (proprioception only) and bimodal (proprioception and vision) conditions. In both areas, time domain and multi-taper spectral analysis methods were used to quantify changes in the spiking, local field potential (LFP), and spike-field coherence during arm-position maintenance.

In both areas, individual neurons were classified based on the spectrum of their spiking patterns. A large proportion of cells in the SPL that exhibited sensory condition-specific oscillatory spiking in the beta (13-30Hz) frequency band. Cells in the IPL typically had a more diverse mix of oscillatory and refractory spiking patterns during the task in response to changing sensory condition. Contrary to the assumptions made in many modelling studies, none of the cells exhibited Poisson-spiking statistics in SPL or IPL.

Evoked LFPs in both areas exhibited greater effects of target location than visual condition, though the evoked responses in the preferred reach direction were generally suppressed in the bimodal condition relative to the unimodal condition. Significant effects of target location on evoked responses were observed during the movement period of the task well.

In the frequency domain, LFP power in both cortical areas was enhanced in the beta band during the position estimation epoch of the task, indicating that LFP beta oscillations may be important for maintaining the ongoing state. This was particularly evident at the population level, with clear increase in alpha and beta power. Differences in spectral power between conditions also became apparent at the population level, with power during bimodal trials being suppressed relative to unimodal. The spike-field coherence showed confounding results in both the SPL and IPL, with no clear correlation between incidence of beta oscillations and significant beta coherence.

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Agent

Created

Date Created
  • 2017