Essential Tremor, Parkinson Disease
Conditions
Brief summary
Individuals experiencing tremors face difficulty performing activities of daily living caused by involuntary oscillation of the muscles in the hands and arms. Current solutions to help suppress tremors include medication, surgery, assistive devices and lifestyle change. However, each of these has a drawback of its own including cost and unwanted side effects. Aside from the solutions listed, it has been shown that functional electrical stimulation (FES) is a possible solution to help suppress tremor. Additionally, FES can be combined with different technologies including accelerometers, gyroscopes and motion capture to develop a closed loop system for tremor suppression. However, this has drawbacks including signal interference and the need for multiple sensor to fully classify the tremor. Ultrasound imaging solves some of these issues because it can provide a direct visualization of hand muscles that contribute to tremor. This study will focus on detecting characterizing and differentiating tremors from voluntary hand motion using ultrasound imaging. The results obtained from this study will help design FES-based tremor-suppression techniques in the future. This study will target both subjects with different tremor disorders and able bodied subjects.
Interventions
DEVICEUltrasound Imaging
We will collect ultrasound images during the grasping motion for both groups
DEVICEElectromyography
We will collect electromyography (EMG) signals of both the flexor and extensor muscles of the wrist during the grasping motion for both groups
DEVICEInertial Measurement Units (IMU)
We will use data from the ultrasound images and EMG to develop a tremor model. The model will be validated in comparison to joint angle measurements from an Inertial Measurement Unit (IMU) collected during the grasping motion
We will use the develop closed-loop control methods for tremor suppression using information from the ultrasound-image based tremor models. FES will be used to provide stimulation that will help with tremor suppression
Sponsors
University of North Carolina, Chapel Hill
North Carolina State University
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
The central objective of this study is to collect experimental data to develop tremor models and suppression methods and validate these methods on participants with tremor. This study is performed with two sets of subjects: people with Parkinson's Disease and Essential Tremor and people without any neurological disorders
Eligibility
Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
Yes
Inclusion criteria
(Tremor Group): 1. At least 40 years of age, and no more than 90 years of age. 2. Meet UK Parkinson's disease brain bank diagnostic criteria 3. Have clinical evidence of rest tremor of one or both upper extremities defined as involuntary, rhythmic oscillations about any joint within the upper extremities 4. Tremor amplitude must be at minimum 1 cm as determined by expert opinion by a movement disorders specialist. 5. Due to the nature of measurements occurring during a grasp maneuver, the tremor must be deemed to become re-emergent with a fixed posture. This shall be defined by development of postural tremor that does not begin immediately upon grasping the vertical object, but instead with a delay in development of oscillatory movement of at least half a second as timed by a stopwatch, and that may grow in amplitude over seconds to maximum amplitude without changing the force of the grasp at first. Note that within-individual intermittency and variability of tremor can be influenced by anxiety, stress, cold temperature, and fatigue. In an effort to reduce this variability, we will have subjects perform tasks in a comfortable area, providing up to 20 minutes to allow them to relax in a temperature-neutral location, and reduce anxiety
Exclusion criteria
(Tremor Group): 1. Muscle weakness as determined by Medical Research Council grade less than 5/5 on direct testing in the upper limb afflicted with rest tremor 2. Infection at the upper limb at time of assessment 3. Pre-existing, concomitant neuromuscular or cerebellar disorders 4. Use of medications that can alter the function of the neuromuscular junction. 5. Those with concomitant essential tremor as determined by history or confirmed by movement disorders specialist prior to assessments. Inclusion Criteria (Able Body): Subjects will fall under the able body category if they exhibit no movement disorders and can perform grasping motion with no inhibition.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Tremor Model Accuracy | Through Completion of Study, an average of 3 years | The investigators will use ultrasound features collected on participants to develop novel models for tremor that can accurately predict the joint position. The joint position measured by the IMU will used as a benchmark and the root mean squared error (RMSE \[Deg.\]) between the model's predicted joint angle and the true angle will be used as a metric. A higher RMSE (in the scale of 0-100%) implies lower model accuracy. |
| Ultrasound Imaging Based Frequency Detection | Through Completion of Study, an average of 3 years | The investigators will benchmark the performance of the ultrasound features (fascicle length \[mm\], muscle thickness \[mm\]) in detecting the actual tremor frequency (Hz) measured by an inertial measurement unit (IMU) sensor and electromyography (EMG). Here error between the tremor frequency measured with IMU and the ultrasound feature-derived tremor frequency is reported. A lower mean error (0-100%) implies higher concurrence with the IMU-derived or EMG-derived tremor frequency. |
| Tremor Suppression (Percentage) | Through Completion of Study, an average of 3 years | The investigators will use the developed tremor models to develop closed loop control methods using FES which enable tremor suppression. The goal of the controller will be to maintain a desired wrist angle position while performing a grasping motion. A tremor suppression ratio metric, formulated as 1-(W\_t/W\_b), where W\_t is the angular velocity of the wrist around the vertical during periods in which stimulation was turned on and W\_b is the angular velocity during baseline periods without any stimulation, is used as an evaluation metric. A higher tremor suppression ratio (0-100%) means higher effectiveness in suppressing the tremor. |
Countries
United States
Participant flow
Recruitment details
2021-recruitment of 1 participant 2022- recruitment of 8 participants 2023- recruitment of 3 participants
Participants by arm
| Arm | Count |
|---|---|
| Tremor Group Individuals with either parkinson's disease or essential tremor will be recruited in this group
Ultrasound Imaging: We will collect ultrasound images during the grasping motion for both groups
Electromyography: We will collect electromyography (EMG) signals of both the flexor and extensor muscles of the wrist during the grasping motion for both groups
Inertial Measurement Units (IMU): We will use data from the ultrasound images and EMG to develop a tremor model. The model will be validated in comparison to joint angle measurements from an Inertial Measurement Unit (IMU) collected during the grasping motion
Functional Electrical Stimulation (FES): We will use the develop closed-loop control methods for tremor suppression using information from the ultrasound-image based tremor models. FES will be used to provide stimulation that will help with tremor suppression | 12 |
| Able Body Group Individuals with no disorders will be recruited in this group
Ultrasound Imaging: We will collect ultrasound images during the grasping motion for both groups
Electromyography: We will collect electromyography (EMG) signals of both the flexor and extensor muscles of the wrist during the grasping motion for both groups
Inertial Measurement Units (IMU): We will use data from the ultrasound images and EMG to develop a tremor model. The model will be validated in comparison to joint angle measurements from an Inertial Measurement Unit (IMU) collected during the grasping motion
Functional Electrical Stimulation (FES): We will use the develop closed-loop control methods for tremor suppression using information from the ultrasound-image based tremor models. FES will be used to provide stimulation that will help with tremor suppression | 0 |
| Total | 12 |
Baseline characteristics
| Characteristic | Tremor Group | Total |
|---|---|---|
| Age, Categorical <=18 years | 0 Participants | 0 Participants |
| Age, Categorical >=65 years | 8 Participants | 8 Participants |
| Age, Categorical Between 18 and 65 years | 4 Participants | 4 Participants |
| Ethnicity (NIH/OMB) Hispanic or Latino | 0 Participants | 0 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 12 Participants | 12 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants | 0 Participants |
| Race (NIH/OMB) Black or African American | 0 Participants | 0 Participants |
| Race (NIH/OMB) More than one race | 0 Participants | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 1 Participants | 1 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants |
| Race (NIH/OMB) White | 11 Participants | 11 Participants |
| Region of Enrollment United States | 12 participants | 12 participants |
| Sex: Female, Male Female | 4 Participants | 4 Participants |
| Sex: Female, Male Male | 8 Participants | 8 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | 0 / 12 |
| other Total, other adverse events | 0 / 12 |
| serious Total, serious adverse events | 0 / 12 |
Outcome results
Primary
Tremor Model Accuracy
The investigators will use ultrasound features collected on participants to develop novel models for tremor that can accurately predict the joint position. The joint position measured by the IMU will used as a benchmark and the root mean squared error (RMSE \[Deg.\]) between the model's predicted joint angle and the true angle will be used as a metric. A higher RMSE (in the scale of 0-100%) implies lower model accuracy.
Time frame: Through Completion of Study, an average of 3 years
Population: Only participants who completed assessment are included.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Tremor Group | Tremor Model Accuracy | Tremor Model Prediction Accuracy with stimulation | 21 Normalized RMSE (%) | Standard Deviation 2.66 |
| Tremor Group | Tremor Model Accuracy | Tremor Model Prediction Accuracy without stimulation | 24 Normalized RMSE (%) | Standard Deviation 4.49 |
Primary
Tremor Suppression (Percentage)
The investigators will use the developed tremor models to develop closed loop control methods using FES which enable tremor suppression. The goal of the controller will be to maintain a desired wrist angle position while performing a grasping motion. A tremor suppression ratio metric, formulated as 1-(W\_t/W\_b), where W\_t is the angular velocity of the wrist around the vertical during periods in which stimulation was turned on and W\_b is the angular velocity during baseline periods without any stimulation, is used as an evaluation metric. A higher tremor suppression ratio (0-100%) means higher effectiveness in suppressing the tremor.
Time frame: Through Completion of Study, an average of 3 years
Population: Only participants who completed these experiments are included in the analysis
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Tremor Group | Tremor Suppression (Percentage) | 62.4 Percentage Suppression | Standard Deviation 18.93 |
Primary
Ultrasound Imaging Based Frequency Detection
The investigators will benchmark the performance of the ultrasound features (fascicle length \[mm\], muscle thickness \[mm\]) in detecting the actual tremor frequency (Hz) measured by an inertial measurement unit (IMU) sensor and electromyography (EMG). Here error between the tremor frequency measured with IMU and the ultrasound feature-derived tremor frequency is reported. A lower mean error (0-100%) implies higher concurrence with the IMU-derived or EMG-derived tremor frequency.
Time frame: Through Completion of Study, an average of 3 years
Population: Only participants who completed assessment are included in the analysis
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Tremor Group | Ultrasound Imaging Based Frequency Detection | Frequency Comparison with IMU | 8.9 Error percentage (%) | Standard Deviation 0.57 |
| Tremor Group | Ultrasound Imaging Based Frequency Detection | Frequency Comparison with EMG | 6.4 Error percentage (%) | Standard Deviation 0.39 |