Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| 101099916 | Other Grant/Funding Number | HORIZON-EIC-2022-PATHFINDEROPEN-01 |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| NEURINNOV | UNKNOWN |
| Institut National de Recherche en Informatique et en Automatique | OTHER |
Not provided
Not provided
Not provided
Not provided
Neurinnov, in collaboration with the CBV USSAP center and the CAMIN INRIA team, has conducted clinical investigations using various control interfaces, including EMG, IMU, contact sensors, and voice commands, to operate a motor neuroprosthesis. This neuroprosthesis is based on neural electrical stimulation, enabling the activation of multiples muscles via a single electrode. The clinical investigations have successfully demonstrated the feasibility of achieving grasping movements induced by neural electrical stimulation, which are controlled by the participant through external interfaces.
These external interfaces were based on existing technologies but were only suitable for research purposes due to their lack of portability. The current investigation aims to validate fully portable interfaces designed by Neurinnov, which are intended to be integral components of a future medical device that includes an implanted stimulator and its neural electrodes. The study's goal is to demonstrate that these interfaces can be used by participants with sufficient success rate (clinical performance) to support daily use.
Our main hypothesis is that the participants can effectively use at least two of the six control interfaces presented to them to detect their intention to perform a motor action within a software environment under constant conditions. These interfaces include voice commands, inertial measurement unit (IMU) sensors, surface electromyography (EMG) sensors, switch, joystick, and earswitch.
Various control interfaces (CIs) are used to capture user intent for operating assistive devices. In recent years, several methods have been developed to detect user intent for controlling invasive motor neuroprostheses for upper limbs. The Freehand System® utilized an external shoulder position sensor on the contralateral side to detect user intent and control hand grasp stimulation. In some studies, a switch was integrated with the sensor to turn the system on and off and to select the type of grasp (palmar or lateral). Brain-computer interface (BCI) systems based on electroencephalography (EEG) have also been employed. The Implantable Stimulator-Telemeter ('IST-10'), the second generation of the Freehand, had ten stimulation channels and was used with an implantable joint angle sensor. The third generation, the Implanted Stimulator Telemeter (IST-12), used myoelectric signals. However, no direct comparison has been made between these different modalities, nor has their relevance been determined.
Therefore, this study aims to evaluate the performance (efficacy: reliability and precision) of six non-invasive control interfaces. The efficacy criterion is defined by the ability to reliably and accurately control a motor action as illustrated by software on a screen. The six control interfaces are: (1) inertial measurement unit (IMU) sensors that record movements of the contralateral shoulder; (2) surface electromyography (EMG) sensors that capture voluntary muscle contractions of the contralateral limb; (3) a pressure sensor button (switch sensor); (4) a pressure sensor joystick (joystick sensor); (5) a voice recognition sensor (voice sensor) that incorporates a machine learning model capable of recognizing specific words spoken by the participant; and (6) an Ear-Switch® sensor that detects movements of a muscle inside the ear, the tensor tympani.
The study will be conducted over six sessions:
(V1) Selection Visit: The selection visit will be conducted by the coordinating investigator, who will monitor the participant throughout the trial.
(V2) Inclusion Visit: This visit will include:
(V3 to V5) Experimental Visits:
(V6) End-of-Study Visit: This final visit will consist of a clinical and psychological follow-up consultation to ensure the absence of any adverse effects.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with complete tetraplegia AIS A or B, with a neurological level ≥ C7 | Experimental |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Comparison of 5 interfaces used to capture user intent to operate a neuroprosthesis | Device | No intervention |
|
| Measure | Description | Time Frame |
|---|---|---|
| Efficacy indicators | Success rate: describes the ability of a control interface to execute requested functions under specified conditions Evaluation criterion: (Number of correctly recognized commands) / (Number of correctly recognized commands + Number of incorrectly recognized commands). Rate in percentage % | At Day 1 |
| Measure | Description | Time Frame |
|---|---|---|
| Time workload indicators | Latency between the user's actual intention and its detection, measured in seconds. | At Day 1 |
| Indicator of feasibility: Ease of installation, calibration, and learning of each control interface (CI) |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Charles FATTAL Charles FATTAL, MD, PhD | Contact | +33 430441100 | cfattal@ussap.fr | |
| David GUIRAUD, PhD | Contact | 33 0434348028 | david.guiraud@neurinnov.com |
| Name | Affiliation | Role |
|---|---|---|
| Charles FATTAL, MD, PhD | Centre Bouffard Vercelli - USSAP | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Rehabilitation Center Bouffard-Vercelli USSAP | Recruiting | Perpignan | 66000 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35029125 | Background | Fattal C, Teissier J, Geffrier A, Fonseca L, William L, Andreu D, Guiraud D, Azevedo-Coste C. Restoring Hand Functions in People with Tetraplegia through Multi-Contact, Fascicular, and Auto-Pilot Stimulation: A Proof-of-Concept Demonstration. J Neurotrauma. 2022 May;39(9-10):627-638. doi: 10.1089/neu.2021.0381. Epub 2022 Feb 2. | |
| 35235517 |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D011782 | Quadriplegia |
| ID | Term |
|---|---|
| D010243 | Paralysis |
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Evaluation criterion: Time tracked by the sensor control software, measured in minutes.
| At Day 2 for the points 1, 2 and 3 and at Day 3 for the point 4 |
| Indicator of feasibility: Ease of placing the control interface | Evaluation criterion: The number of times a third party (participant's caregiver or clinician) needed physical assistance and/or requested additional instructions to position the sensor. | At Day 2 for the points 1, 2 and 3 and at Day 3 for the point 4 |
| Indicator of feasibility: Ease of learning to use the control interface | Evaluation criterion: The number of repetitions required for the participant to learn the interface. At Day 2 for the points 1, 2 and 3 and at Day 3 for the point 4 | At Day 2 for the points 1, 2 and 3 and at Day 3 for the point 4 |
| Indicator of feasibility: User feedback concerning usability of the control interface | Evaluation criterion: System Usability Scale French Version (F-SUS) Score min: 10 and score max: 50 | At Day 2 for the points 1, 2 and 3 and at Day 3 for the point 4 |
| Indicator of tolerance : Pain experienced during and after using the interface | Evaluation criterion: visual analog scale (VAS) ranging from 0 to 10. | During the experimentation at Day 2 and 3 |
| Indicator of tolerance : Adverse effects | Adverse effects encountered during and after using the interface. | During the experimentation at Day 2 and 3 |
| Indicators of satisfaction, comfort, pleasure of use and subjective workload | User satisfaction with the control interface (CI) Evaluation criterion: Quebec User Evaluation of Satisfaction with Assistive Technology (French version = ESAT) . Score min : 12 and score max: 60 | At Day 3 |
| Indicators of satisfaction, comfort, pleasure of use and subjective workload | Enjoyability of the control interface, reflecting the user's mood, motivation, or frustration. Evaluation criterion: appropriate section of the questionnaire National Aeronautics and Space Administration Task Load Index (NASA-TLX). For each item, the score min is 0 and max 100 | At Day 3 |
| Indicators of satisfaction, comfort, pleasure of use and subjective workload | User perception of subjective workload Evaluation criterion: questionnaire National Aeronautics and Space Administration Task Load Index (NASA-TLX). For each item, the score min is 0 and max 100 | At Day 3 |
| Indicators that a static and dynamic intensity value has been reached in a predetermined time (difference between target and initial value) | Static trial: successful target acquisition within the allotted time (acquisition time in seconds). | At Day 7 |
| Indicators that a static and dynamic intensity value has been reached in a predetermined time (difference between target and initial value) | 2. Dynamic trial: the user-controlled value remains within a 10% margin of error relative to the reference value throughout the trial. (margin of error in percentage %) | At Day 7 |
| Fonseca L, Guiraud D, Hiairrassary A, Fattal C, Azevedo-Coste C. A Residual Movement Classification Based User Interface for Control of Assistive Devices by Persons With Complete Tetraplegia. IEEE Trans Neural Syst Rehabil Eng. 2022;30:569-578. doi: 10.1109/TNSRE.2022.3156269. Epub 2022 Mar 21. |
| 32429963 | Background | Tigra W, Dali M, William L, Fattal C, Gelis A, Divoux JL, Coulet B, Teissier J, Guiraud D, Azevedo Coste C. Selective neural electrical stimulation restores hand and forearm movements in individuals with complete tetraplegia. J Neuroeng Rehabil. 2020 May 19;17(1):66. doi: 10.1186/s12984-020-00676-4. |
| 30441476 | Background | Fonseca L, Bo A, Guiraud D, Navarro B, Gelis A, Azevedo-Coste C. Investigating Upper Limb Movement Classification on Users with Tetraplegia as a Possible Neuroprosthesis Interface. Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:5053-5056. doi: 10.1109/EMBC.2018.8513418. |
| 31635286 | Background | Fonseca L, Tigra W, Navarro B, Guiraud D, Fattal C, Bo A, Fachin-Martins E, Leynaert V, Gelis A, Azevedo-Coste C. Assisted Grasping in Individuals with Tetraplegia: Improving Control through Residual Muscle Contraction and Movement. Sensors (Basel). 2019 Oct 18;19(20):4532. doi: 10.3390/s19204532. |
| 36202865 | Background | Coste CA, William L, Fonseca L, Hiairrassary A, Andreu D, Geffrier A, Teissier J, Fattal C, Guiraud D. Activating effective functional hand movements in individuals with complete tetraplegia through neural stimulation. Sci Rep. 2022 Oct 6;12(1):16189. doi: 10.1038/s41598-022-19906-x. |
| D013568 |
| Pathological Conditions, Signs and Symptoms |