Clinical trial NCT04889586: Hand MOtor Rehabilitation Using a EMG-biofeedback: a Cross-sectional Study
Official title: Hand Motor Recovery Using a EMG-biofeedback in Stroke Rehabilitation: a Cross-sectional Study
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Stroke
Stroke Hemorrhagic
Stroke, Ischemic
Hemiparesis
Hemiplegia
Keywords: Neurological Rehabilitation
Upper Extremity
Electromyography
Hand Gesture
Lead sponsor: IRCCS San Camillo, Venezia, Italy
Sponsor class: OTHER
First posted: 2021-05-17
Enrollment: 100
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Each subject is assessed with a clinical protocol and an instrumental test, consists in executing 10 hand gestures by wearing a EMG-biofeedback armband
Primary purpose: SCREENING

Brief summary: Recovery of upper limb and hand gestures is fundamental for autonomy restoration after stroke. Innovative technologies are a valid support for the delivery of rehabilitation treatments. Embedding surface electromyographic (sEMG) into wearable devices, allows the customisation of rehabilitation exercises, based on the clinical profile of each patient.

Detailed description: The aims of this study are to determine safety and feasibility of a prototype EMG-control wearable device (REMO) and to individualise clinical features of stroke survivors able to control the EMG armband targeted to hand rehabilitation.

The device REMO consists in an armband composed by 8 bipolar electrodes able to record and process the electromyography of forearm muscles. The patterns of muscle activations are classified and used to perform EMG-biofeedback exercises in stroke rehabilitation training. The device is developed by clinicians of IRCCS San Camillo Hospital and spin-off Morecognition Srl.

A total of 100 stroke patients patients has been recruited. They are clinically assessed and then tested on the ability to control the sEMG wearable device. The test is composed of 10 hand and fingers gestures to be performed with the paretic hand. Baseline and activation sEMG signals are recorded and compared for each movement. Three conditions representing absent, partial or full control of the device are defined and logistic multivarialbes regression models are used to identify clinical features describing the group each patient belongs to. Clinical cut-off for each strata is identified by odds ratio.

Eligibility criteria: Inclusion Criteria:

* Single ischemic or haemorrhagic stroke;
* Score lower than 100 out of a total of 126 at the Functional Independence Measure (FIM) scale

Exclusion Criteria:

* Untreated epilepsy;
* Major depressive disorder;
* Fractures;
* Traumatic Brain Injurj;
* Severe Ideomotor Apraxia;
* Severe Neglect;
* Severe impairment of verbal comprehension.

Primary outcomes:
measure: Fugl-Meyer Upper Extremity (FMA-UE)
timeFrame: within 1 week from enrolment.
Secondary outcomes:
measure: Fugl-Meyer - sensation
timeFrame: within 1 week from enrolment.
measure: Fugl-Meyer - pain and Range of Motion
timeFrame: within 1 week from enrolment.
measure: Box and Blocks Test (BBT)
timeFrame: within 1 week from enrolment.
measure: Reaching Performance Scale (RPS)
timeFrame: within 1 week from enrolment.
measure: Modified Ashworth Scale (MAS)
timeFrame: within 1 week from enrolment.
measure: Nine Hole Pegboard Test (NHPT)
timeFrame: within 1 week from enrolment.
measure: Functional Independence Measure scale (FIM)
timeFrame: within 1 week from enrolment.
measure: Number of movements controlled by EMG-biofeedback device
timeFrame: within 1 week from enrolment.
Other outcomes:
Locations:
city: Venice-Lido
country: Italy
facility: IRCCS San Camillo Hospital
state: Venice
Study officials:
affiliation: IRCCS San Camillo Hospital
name: Andrea Turolla, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Celadon N, Dosen S, Binder I, Ariano P, Farina D. Proportional estimation of finger movements from high-density surface electromyography. J Neuroeng Rehabil. 2016 Aug 4;13(1):73. doi: 10.1186/s12984-016-0172-3.
citation: Dipietro L, Ferraro M, Palazzolo JJ, Krebs HI, Volpe BT, Hogan N. Customized interactive robotic treatment for stroke: EMG-triggered therapy. IEEE Trans Neural Syst Rehabil Eng. 2005 Sep;13(3):325-34. doi: 10.1109/TNSRE.2005.850423.
citation: Paleari M, Di Girolamo M, Celadon N, Favetto A, Ariano P. On optimal electrode configuration to estimate hand movements from forearm surface electromyography. Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:6086-9. doi: 10.1109/EMBC.2015.7319780.
citation: Pollock A, Farmer SE, Brady MC, Langhorne P, Mead GE, Mehrholz J, van Wijck F. Interventions for improving upper limb function after stroke. Cochrane Database Syst Rev. 2014 Nov 12;2014(11):CD010820. doi: 10.1002/14651858.CD010820.pub2.