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Pregnolato G1, Baldan F1, Maistrello L1, Berlingieri C1, Alhelou M1, Di Girolamo M2, Favetto A2, Celadon N2,3, Ariano P2,3, Turolla A1
1Fondazione Ospedale San Camillo IRCCS, Laboratory of Neurorehabilitation Technologies, Venice, Italy, 2Fondazione Istituto Italiano di Tecnologia, Artificial Physiology Group, Centre for Sustainable Future Technologies, Turin, Italy, 3Morecognition Srl, Turin, Italy
Background: Stroke is the first cause of permanent disability worldwide and recovery of hand function still remains the hardest target to achieve in neurorehabilitation. Evidence exists that both intensity and specificity of motor exercises are the main drivers for effective treatment modalities after stroke. Surface Electromyography (sEMG) biofeedback provides information to patients about timing and amplitude of their muscles activation in the form of visual and/or auditory amplification of their sEMG signal.
Purpose: The aim of the study was to investigate the efficacy of a task-specific training with a sEMG biofeedback armband for motor hand recovery in people with a stroke.
Methods: The device is a wearable armband developed by the Istituto Italiano di Tecnologia in collaboration with Morecognition Srl and the IRCCS San Camillo Hospital Foundation. The device is composed by 8 dry bipolar sEMG electrodes able to detect muscles activation at the level of patients' forearm. Then, through real-time processing, the main components of the acquired sEMG are extracted and exploited for controlling artificial environments. The patients after first single stroke and without severe cognitive impairments were enrolled and assessed before and after the training with the following scales: Fugl-Meyer Upper Extremity (F-M UE), Functional Independence Measure (FIM), Reaching Performance Scale (RPS), Box and Block Test (BBT), Modified Ashworth Scale (MAS), Nine Hole Pegboard Test (NHPT). The training consists in task-specific exercises controlled by sEMG biofeedback provided by the armband connected to a PC interface; the treatment comprehended 15 session (1 hour/day), for 3 weeks, 5 times/week.
Descriptive and inferential analyses were conducted to define significant improvements. Statistical threshold was set at p 0.05. Furthermore, analyses were conducted to investigate different clinical outcome driven by lesion site (right/left hemisphere) or time from lesion (before/ after 4 months).
Results: 19 patients were enrolled and completed the treatment. Significant improvements were found for: FM UE motor section (6.1 points on average, p=0.026), BBT (6.26 blocks on average, p=0.007), RPS (4.1 points on average, p=0.017) and FIM (7.4 points on average, p=0.005). Patients with lower number of months from lesion (≤ 4 months) has better recovery in FIM assessment (14 points on average, p=0.003). No differences were found between patients with lesion in the right or left hemisphere.
Conclusion(s): The results show that training provided by sEMG biofeedback armband could provide an effective gain of motor recovery for patients with impairments of upper limb motor function. In acute phase after stroke, the training may contribute to improve autonomy in ADLs.
Implications: The sEMG biofeedback armband could be a valid modality for improving motor function of upper limb after stroke. The device is comfortable and easy to use, for both clinician and patient. For future applications, the same device could be used as a sEMG-based controller also for other rehabilitation technologies or for control of domotics environment.
Keywords: Neurorehabilitation, Hand Function, Motor Recovery
Funding acknowledgements: None.
Purpose: The aim of the study was to investigate the efficacy of a task-specific training with a sEMG biofeedback armband for motor hand recovery in people with a stroke.
Methods: The device is a wearable armband developed by the Istituto Italiano di Tecnologia in collaboration with Morecognition Srl and the IRCCS San Camillo Hospital Foundation. The device is composed by 8 dry bipolar sEMG electrodes able to detect muscles activation at the level of patients' forearm. Then, through real-time processing, the main components of the acquired sEMG are extracted and exploited for controlling artificial environments. The patients after first single stroke and without severe cognitive impairments were enrolled and assessed before and after the training with the following scales: Fugl-Meyer Upper Extremity (F-M UE), Functional Independence Measure (FIM), Reaching Performance Scale (RPS), Box and Block Test (BBT), Modified Ashworth Scale (MAS), Nine Hole Pegboard Test (NHPT). The training consists in task-specific exercises controlled by sEMG biofeedback provided by the armband connected to a PC interface; the treatment comprehended 15 session (1 hour/day), for 3 weeks, 5 times/week.
Descriptive and inferential analyses were conducted to define significant improvements. Statistical threshold was set at p 0.05. Furthermore, analyses were conducted to investigate different clinical outcome driven by lesion site (right/left hemisphere) or time from lesion (before/ after 4 months).
Results: 19 patients were enrolled and completed the treatment. Significant improvements were found for: FM UE motor section (6.1 points on average, p=0.026), BBT (6.26 blocks on average, p=0.007), RPS (4.1 points on average, p=0.017) and FIM (7.4 points on average, p=0.005). Patients with lower number of months from lesion (≤ 4 months) has better recovery in FIM assessment (14 points on average, p=0.003). No differences were found between patients with lesion in the right or left hemisphere.
Conclusion(s): The results show that training provided by sEMG biofeedback armband could provide an effective gain of motor recovery for patients with impairments of upper limb motor function. In acute phase after stroke, the training may contribute to improve autonomy in ADLs.
Implications: The sEMG biofeedback armband could be a valid modality for improving motor function of upper limb after stroke. The device is comfortable and easy to use, for both clinician and patient. For future applications, the same device could be used as a sEMG-based controller also for other rehabilitation technologies or for control of domotics environment.
Keywords: Neurorehabilitation, Hand Function, Motor Recovery
Funding acknowledgements: None.
Topic: Robotics & technology; Neurology: stroke; Disability & rehabilitation
Ethics approval required: Yes
Institution: Fondazione Ospedale San Camillo IRCCS, Venezia, Italia.
Ethics committee: Ethics Committee for Experimentation of ULSS12 and IRCCS San Camillo.
Ethics number: CE cod. 2016.29 – More
All authors, affiliations and abstracts have been published as submitted.
