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| Name | Class |
|---|---|
| IRCCS Istituto Ortopedico Rizzoli di Bologna | UNKNOWN |
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The investigators propose to validate a non-invasive upper limb prosthesis capable of combining: 1) intuitive movement control through machine learning applied to myoelectric signals, and 2) vibrotactile sensory feedback in response to touch and object release events. The prosthesis is composed at the minimum of skin-surface electrodes for myoelectric signals, vibrotactile actuators, a multi-articulated and instrumented hand prosthesis and a centralized control system. Such system is validated for several weeks in non-supervised environments.
The investigators propose a pilot single-center study, randomized with crossover design to compare the intuitive control strategy with the standard-in-care direct control strategy.
Primary Objectives The primary objective is to validate a non-invasive, transradial prosthesis that integrates the latest advancements for intuitive, bidirectional and multi-articulated control. This validation is intended to be conducted in unsupervised environments (i.e., home-use). The prosthesis under validation combines intuitive movement control through pattern recognition applied to myoelectric signals, and vibrotactile sensory feedback in response to touch and object release events.
The validation is conducted through well-established functional tests in the field designed to measure dexterity and motor coordination, and through data on daily usage.
Secondary Objectives The secondary objective is to validate the proposed prosthesis based on subjective assessments regarding user satisfaction, perceived capacity to control the device, and perceived level of disability.
Additionally, the study aims to assess whether participation in this research has any impact on the control of the clinically used prosthesis. To this end, both functional tests and self-assessment questionnaires will be used to evaluate the clinical prosthesis before and after the trial protocol.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| machine learning based prosthesis control | Experimental | A non-invasive upper limb prosthesis whose control is facilitated through machine learning applied to myoelectric signals. The movements on the prosthesis are triggered by intuitive muscular contractions performed at the residual limb. |
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| conventional direct control | Active Comparator | A non-invasive upper limb prosthesis whose control is enable by standard-in-care movement control strategy. The movements on the prosthesis are sequentially triggered through simple thresholds applied to myoelectric signals. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Prosthetic controller | Device | The intervention includes an upper limb prosthesis composed at the minimum by skin-surface electrodes for myoelectric signals, a vibrotactile actuator, a multi-articulated and instrumented hand prosthesis and a centralized control system. The centralized prosthetic controller processes the myoelectric signals acquired at the residual limb to enable the movements on the multi-articulated prosthesis. |
| Measure | Description | Time Frame |
|---|---|---|
| Southampton Hand Assessment Procedure (SHAP) | The test consists of sequentially manipulating 6 lightweight and 6 heavyweight abstract objects and 14 activities of daily living over a specific formboard. Lightweight objects should be manipulated first. The task involves pushing a button to start a timer, picking up and moving the object from the rear slot to the front slot on the board, and completing the task by depressing the button on the timer again. | Measured at the baseline with the clinical prosthesis already in use (if any), then measured at the first and last week of each home-trial. Lastly, measured again after at least 1 wash-out week from the last home-trial |
| Clothespin Relocation Test (CRT) | The objective is to evaluate the performance of a prosthetic user in a controlled environment and subsequently provide a measure of the user's expected functionality level outside the laboratory/clinic. The user is instructed to allocate three clothespins between a horizontal rod and a vertical rod and asked to fill out a post-test survey after five trials of the CRT. | Measured at the baseline with the clinical prosthesis already in use (if any), then measured at the first and last week of each home-trial. Lastly, measured again after at least 1 wash-out week from the last home-trial |
| Pick and Lift Test (PLT) | The PLT measures motor coordination, i.e., the ability to coordinate the grip force and the load force while lifting an object, as well as the reliability of the recorded control signal while transporting the object. While the subject is sitting on a chair with the intact arm parallel to the trunk, and the amputated limb extending anteriorly on a table, he/she is asked to lift a small object from the table with the prosthesis. | Measured at the baseline with the clinical prosthesis already in use (if any), then measured at the first and last week of each home-trial. Lastly, measured again after at least 1 wash-out week from the last home-trial |
| Virtual Egg Test (VET) |
| Measure | Description | Time Frame |
|---|---|---|
| NASA-TLX questionnaire | The NASA-TLX is a questionnaire to assess subjective workload, in terms of mental, physical, temporal, performance, effort and frustration. The resulting score ranges from 0 to 100, where 0 means no workload (very easy) and 100 means maximum workload (extremely demanding). | Administered after each functional test (primary outcomes). Measured at the baseline with the clinical prosthesis already in use (if any), then measured at the first and last week of each home-trial. Lastly, measured again at the end of the study |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Enzo Mastinu, MSc, BSc, PhD | Contact | 0039 050 883111 | enzo.mastinu@santannapisa.it |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| IRCCS Istituto Ortopedico Rizzoli | Recruiting | Bologna | Bo | 40136 | Italy |
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The investigators propose a pilot single-center study, randomized with crossover design to compare the intuitive control strategy with the standard-in-care direct control strategy. Each condition will be assessed with a 4 weeks home-trial, separated by at least 1 wash-out week.
Each condition will dispose of a non-invasive upper limb prosthesis composed at the minimum of skin-surface electrodes for myoelectric signals, a multi-articulated and instrumented hand prosthesis, a vibrotactile actuator enabled at touch/release of the objects, and a centralized control system. The two conditions will differ based on the movement control strategy, machine learning based as opposed to conventional threshold control. The former tries to simplify the control of all degrees of freedom available by decoding intuitive muscular contraction at the residual limb. The latter applies simple thresholds to the myoelectric signals to provide sequential activations of all degrees of freedom available.
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The VET resembles the task of transporting fragile and robust objects, thus requiring both gross and fine dexterity. The test is composed of 11 Virtual Eggs that collapse if the grasping force exceeds their breaking thresholds, ranging from 0.4 N to 11.5 N. The test aims to transport each Virtual Egg over the barrier in the centre of the test platform without breaking it and as fast as possible. The metrics measured during the test are combined and provide two indexes that evaluate, respectively, gross and fine dexterity.
| Measured at the baseline with the clinical prosthesis already in use (if any), then measured at the first and last week of each home-trial. Lastly, measured again after at least 1 wash-out week from the last home-trial |
| Usage of the prosthesis | The prosthesis, for as long as it is powered, will log real-time information about its usage during the day. Such data will allow us to calculate the total wear/use time, as well as the quality of the usage (which moments are used and how often). The data should also provide basic information for debugging in case of system failures and adverse events. | Usage data will be recorded by the prosthesis during the two 4 weeks home-trials |
| abilHAND-ULA | The abilHAND-ULA is a questionnaire for self-assessing the perceived manual ability for individuals with upper limb amputation. The cumulative score ranges from 0 to 66, with higher scores indicating better manual ability. | Administered before, after and at each week of the two home-trials |
| OPUS-UEFS | The Orthotics and Prosthetics User's Survey - Upper Extremity Functional Scale for Prosthesis Users (OPUS-UEFS) is a self-report measure designed to assess the functional status of individuals using upper limb prostheses, considering the level of amputation and prosthesis type. Each of the 23 items is rated on a 5-point scale (0 = cannot do this activity, 5 = very easy). The cumulative score ranges from 0 to 92, with higher scores indicating greater functional ability. | Administered before, after and at each week of the two home-trials |
| TAPES | The Trinity Amputation and Prosthesis Experience Scales (TAPES) is a self-administered questionnaire that comprises psychosocial adjustment, activity restriction, and prosthetic satisfaction domains, each with 3 subscales. Each subscale is scored individually, with higher scores consistently indicating more positive outcomes. Summing scores across different subscales is not appropriate. | Administered before, after and at each week of the two home-trials |
| QuickDASH | The Disability of the Arm, Shoulder and Hand is a self-administered questionnaire aimed at evaluating upper limb function. It is a 30-item questionnaire (main section) where each item is rated from 1 to 5 for increased difficulty/severity. The overall score ranges from 0 to 100. | Administered before, after and at each week of the two home-trials |
| SUS | The System Usability Scale (SUS) is a ten-item attitude Likert scale giving a global view of subjective assessment of usability. Users respond to 10 statements, rating them from 1 (Strongly Disagree) to 5 (Strongly Agree). The higher the score, the higher the perceived usability. Usually a score of 68 is the average industrial benchmark, and a score >80 is considered as excellent. | Administered before, after and at each week of the two home-trials |