In this study the effects of diabetic peripheral neuropathy will be assessed on balance control, balance recovery, and muscle electrical activity in adults over 50 years.
Aim 1: Determine muscle activity and balance control during a sit-to-stand in adults age above 50 with and without diabetic peripheral neuropathy.
Aim 2: Assess local balance recovery and latency responses to lateral surface perturbation during quiet standing.
Type II diabetes with peripheral neuropathy
Foot ulcer
Partial amputation
Have experience of Stroke
Painful neuropathy
Parallel
sit-to-stand
Behavioraltest for balance during movement from sitting to standing
stand to sit
Behavioraltest for balance during movement from standing to sitting
standing perturbation
Behavioraltest for balance recovery following perturbation
MRI of sciatic nerve
Other interventionmeasure of peripheral nerve diameter
Center of pressure using force plate
Center-of-pressure sway will be assessed between groups. As participants sit down or stand up from a chair on the force plates, the ground reaction force will be collected. Then, using a mathematical approach, an ellipse will be fitted to the data to calculate the sway area. A higher sway area indicates an impairment during balance control.
Center of mass using Vicon cameras.
Center-of-mass sway volume will be assessed as the participant will walk in front of a high-speed camera, which will be recorded using the retroreflective markers. Then, a mathematical approach will be used to fit an ellipsoid to the data samples for each group. Higher sway volume means impairment in balance.
Joint moment using Nexus software
Joint moments will be assessed between groups using Vicon and force plates. This variable will be obtained using Nexus software, which combines both the inputs from Vicon and force plates.
Local dynamic stability using Motek and Vicon system
Local dynamic stability will be assessed using the Motek treadmill and Vicon cameras. The Motek treadmill will provide the left and right perturbation, and the Vicon system will collect the kinematic data. Then, the MATLAB code will calculate local dynamic stability to identify impairment in balance recovery.
Muscle amplitude using root mean square
Muscle amplitude will be collected using Delsys Tringo wireless surface electromyography (EMG). The EMG electrodes will be attached with double adhesive tape. Then, EMG amplitudes will be assessed using the root mean square technique in MATLAB software. Higher amplitude represents higher muscle activity.
Muscle onset time using electromyography
The muscle onset time will be assessed using MATLAB code. An abrupt change in the EMG trace is defined as a muscle onset time. Any change in EMG onset time represents impairment in neuromuscular junctions or muscle and nerve electrical conduction.
Muscle co-activation index using EMG
The coactivation index will be assessed between two muscles in the same participant using MATLAB syntax. An increase in muscle coactivation represents an increase in active joint stiffness. This increase in active joint stiffness reduces the resultant joint moment, leading to impaired smoothness of movement and reducing the ability to perform daily activities.
Muscle energy frequency using EMG data
Wavelet transform can identify the contribution of different muscle fibers (large or small, fast or slow twitch fibers) in the same task. Assessment of this method indicates what fiber type is affected by DPN.
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Lisa Griffin
Lead sponsor
University of Texas at Austin
Sponsor institution
