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The study is a pilot feasibility study aimed at verifying that (1) tremor can be recognized using an accelerometer placed on the hand area and a data mining algorithm properly trained and (2) TENS applied in the hand area is able to acutely suppress hand tremor respect to the baseline.
The study includes 2 different groups: 9 patients with Parkinson's disease with resting tremor alone at the start of their disease (group1), and 5 patients with Essential Tremor (group2). For both groups, the study protocol includes an initial screening visit, in which, after enrollment, the patient's baseline is defined. The experimental session combines both tremor recording and a TENS stimulation treatment.
During the experimental session, the patient wears two devices able to record the upper limb's motion. These devices are commercially available wearable IMU sensors equipped with a triaxial accelerometer, a triaxial gyroscope and triaxial magnetometer. One device is located on the hand, the other on the wrist of the same upper limb, the dominant one. Patients are asked to perform the tasks of the WHIGET scale at baseline and during two different types of electrical stimulation (in a randomly assigned order).
For the recording part, the primary endpoint is the accuracy of the detection system measured as the number of correct detections of tremor episodes on the total tremor episodes recorded by the system (5 seconds windows). For the stimulation part, the primary endpoint is the reduction of upper limb tremor during the stimulation session compared to baseline.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Parkinson'Disease | Experimental | Patients with Parkinson's disease with resting tremor alone at the start of their disease |
|
| Essential Tremor | Experimental | Patients with Essential Tremor |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| JAME | Device | JAME is a wearable device able to monitor movements of the upper limbs and, through an ad-hoc algorithm based on machine learning, can recognize tremor and suppress it through TENS |
| Measure | Description | Time Frame |
|---|---|---|
| tremor recognition | For the recording part, the primary endpoint is the accuracy of the detection system measured as the number of correct detections of tremor episodes on the total tremor episodes recorded by the system (5 seconds windows); | 10 minutes |
| tremor suppression | the primary endpoint is the reduction of upper limb tremor during the stimulation session compared to baseline, measured with the WHIGET scale | 10 minutes |
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Inclusion Criteria:
Subject signed the approved Informed Consent;
Subject is willing and able to complete the study procedures;
Subject is ≥ 18 years of age;
Subject has a certain diagnosis of:
Subject has a normal cognitive function (MMSE ≥ 24 or MoCA >26).
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Linda Borellini, MD | Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Linda Borellini | Milan | Italy | 20122 | Italy |
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| ID | Term |
|---|---|
| D010300 | Parkinson Disease |
| D020329 | Essential Tremor |
| ID | Term |
|---|---|
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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open label pilot study
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| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |