Engineering Commons^™

Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon

Electronic Thesis and Dissertation Repository

Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.

One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …

Motion Intention Estimation Using Semg-Acc Sensor Fusion, Jose Alejandro Lopez

Electronic Thesis and Dissertation Repository

Musculoskeletal injuries can severely impact the ability to produce and control body motion. In order to regain function, rehabilitation is often required. Wearable smart devices are currently under development to provide therapy and assistance for people with impaired arm function. Electromyography (EMG) signals are used as an input to pattern recognition systems to determine intended movements.

However, there is a gap between the accuracy of pattern recognition systems in constrained laboratory settings, and usability when used for detecting dynamic unconstrained movements. Motion factors such as limb position, interaction force, and velocity, are known to have a negative impact on the …

A Biomechanical And Physiological Signal Monitoring System For Four Degrees Of Upper Limb Movement, Allison R. Goldman

Electronic Thesis and Dissertation Repository

A lack of adherence to prescribed physical therapy regimens in improper healing results in poor outcomes for those affected by musculoskeletal disorders (MSDs) of the upper limb. Societal and psychological barriers to proper adherence can be addressed through the system presented in this work consisting of the following components: an ambulatory biosignal acquisition sleeve, an electromyography (EMG) based motion repetition detection algorithm, and the design of a compatible capacitive EMG acquisition module.

The biosignal acquisition sleeve was untethered, unobtrusive to motion, contained only modular components, and collected biomechanical and physiological sensor data to form full motion profiles of the following …

Dynamic Calibration Of Emg Signals For Control Of A Wearable Elbow Brace, Taylor Stanbury

Electronic Thesis and Dissertation Repository

Musculoskeletal injuries can severely inhibit performance of activities of daily living. In order to regain function, rehabilitation is often required. Assistive devices for use in rehabilitation are an avenue explored to increase arm mobility by guiding therapeutic exercises or assisting with motion. Electromyography (EMG), which are the muscle activity signals, may be able to provide an intuitive interface between the patient and the device if appropriate classification models allow smart systems to relate these signals to the desired device motion.

Unfortunately, there is a gap in the accuracy of pattern recognition models classifying motion in constrained laboratory environments, and large …

Development Of An Emg-Based Muscle Health Model For Elbow Trauma Patients, Emma Farago

Electronic Thesis and Dissertation Repository

Musculoskeletal (MSK) conditions are a leading cause of pain and disability worldwide. Rehabilitation is critical for recovery from these conditions and for the prevention of long-term disability. Robot-assisted therapy has been demonstrated to provide improvements to stroke rehabilitation in terms of efficiency and patient adherence. However, there are no wearable robot-assisted solutions for patients with MSK injuries. One of the limiting factors is the lack of appropriate models that allow the use of biosignals as an interface input. Furthermore, there are no models to discern the health of MSK patients as they progress through their therapy.

This thesis describes the …

Skills Assessment In Arthroscopic Surgery By Processing Kinematic, Force, And Bio-Signal Data, Behnaz Poursartip

Electronic Thesis and Dissertation Repository

Arthroscopic surgery is a type of Minimally Invasive Surgery (MIS) performed in human joints, which can be used for diagnostic or treatment purposes. The nature of this type of surgery makes it such that surgeons require extensive training to become experts at performing surgical tasks in tight environments and with reduced force feedback. MIS increases the possibility of erroneous actions, which could result in injury to the patient. Many of these injuries can be prevented by implementing appropriate training and skills assessment methods.

Various performance methods, including Global Rating Scales and technical measures, have been proposed in the literature. However, …

Elbow Patients’ Data Collection And Analysis: An Examination Of Electromyography Healing Patterns, Raneem Haddara

Electronic Thesis and Dissertation Repository

Musculoskeletal conditions are the most common cause of severe long-term pain and physical disability, accounting for the highest disability costs of about $17 billion yearly. To provide better rehabilitation tactics, the knowledge gap between injuries and their healing mechanisms needs to be addressed. The use of electromyography (EMG) is very popular in detecting neuromuscular diseases or nerve lesions; however, there is limited knowledge available for quantifying healing patterns of EMG in orthopedic patients who have injured their joints, muscles, or bones. In order to quantify the progress of orthopedic patients and assess their neuromuscular health and muscle synergy patterns, EMG …