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The use of home automation system may be useful in rehabilitation to collect data about the environment and the amount of therapy. Then, the data may be stored in a cloud and integrated with data collected during training provided by technological devices.
The main goal of this longitudinal pilot study is to define the productivity of the rehabilitation room (i.e., HoSmartAI room) in the IRCCS San Camillo Hospital (Venice, Italy) service, where the investigators will install home automation sensors and treat patients with neurological disease using technological devices (e.g., robotic and virtual reality). The secondary goals are to define the patients' satisfaction, usability of the system and the clinical effect of treatments delivered with technological devices in the HoSmartAI room. The patient will be assessed to personalized the treatment based on their needs. The treatment will consist of 15 sessions (1h/day, 5day/week, 3 weeks). At the end of the study, the patients will be assessed to define any clinical improvements. Finally, the investigators will define the characteristics of the patients who will benefit from the rehabilitation provided in the HoSmartAI room.
The recovery of motor function is a primary goal for individuals diagnosed with neurological disease, such as Stroke, Parkinson's Disease, Multiple Sclerosis. Various rehabilitation methods have been using in neurorehabilitation hospital, including conventional training and those involving technological devices. Nowadays, the integration of technology into rehabilitation room has been expanding within the National Health System, and their effectiveness in enhancing functionality and quality of life remains a subject of ongoing research in rehabilitation. In addition to rehabilitation devices, such as robotic and virtual reality systems, home automation system may play a crucial role in monitoring and recording patient movements. These sensors can also be employed for home automation in environments such as hospital rehabilitation settings, helping to reduce paid carer hours, quantify the impact of automated data acquisition on the functionality and offer many benefits to people with a disability. Indeed, potentially, the application of home automation system in technological rehabilitation rooms, may allow for the synchronization of environmental data with the patient's clinical history, facilitating the study of functional recovery.
This study is a part of the HosmartAI project (EU Horizon 2020 research and innovation program - grant agreement No 101016834 Pilot #3). The main aim of HoSmartAI project is to develop hospitals based on artificial intelligence (AI) technologies. In Pilot #3, the investigators will integrate data collected by technological devices for motor rehabilitation and home automation sensors installed in room (HosmartAI room) at the Neuromotor Rehabilitation Service of the San Camillo IRCCS Hospital (Venice, Italy). These sensors are able to detect the effective numbers of minutes of therapy, the number of sessions delivered in the room, and detect the presence and falls of the patients. Moreover, all these sensors are managed directly by physiotherapists through an App for smartphone. All data collected will be integrated in a cloud infrastructure, where physiotherapist will check the patients' profile and data collected from clinical assessment and home automation sensors.
In the study, the investigators will enroll patients with neurological disease and motor impairment who are hospitalized in Camillo IRCCS Hospital (Venice, Italy). The treatment (5time/week, for 3 weeks) will consist of 1 hour/day of motor training provided by technological devices (i.e., OAK, VRRS, AMADEO, PABLO) in the HoSmartAI room, in addition to daily 1 hour of conventional motor training. Firstly, the patients will be assessed to define their motor function and personalize the treatment based on their needs, to improve balance, manual dexterity, or upper and lower limb motor recovery. Then, at the end of the treatment, the patients will be assessed using validated clinical scales and questionnaire to determine the clinical effect and patient-reported outcome measurements (i.e., usability, technology acceptability, and user satisfaction).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| HosmartAI training | Experimental | HosmartAI training will consist of motor training provided by technological devices (i.e. OAK, VRRS, AMADEO, PABLO) in the HoSmartAI room. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Technological Motor Rehabilitation | Device | Patients will undergo to motor treatment in the HoSmartAI room using one of the technological devices (i.e. OAK, VRRS Evo by Khymeia Group, Padova, Italy; AMADEO, PABLO by Tyromotion GmbH, Gratz, Austria), for the upper limb and lower limb motor recovery, balance and manual dexterity recovery. The duration of the treatment will be 15 sessions, 1 hour each, with daily frequency, 5 days a week, for a total of 3 weeks. |
| Measure | Description | Time Frame |
|---|---|---|
| Key performance indicator (KPI) of the room - Number of treatments | Number of treatments that are provided inside the HoSmartAI room. | Every month up to 1 year |
| Key performance indicator (KPI) ot the room - Number of sessions | Number of sessions that are provided inside the HoSmartAI room. | Every month up to 1 year |
| Room Key performance indicator (KPI) of the room - Number of minutes of therapy | Number of minutes of therapy that are provided inside the HoSmartAI room. | Every month up to 1 year |
| Key performance indicator (KPI) of the room - Number of physiotherapists involved | Number of physiotherapists involved inside the HoSmartAI room. | Every month up to 1 year |
| Key performance indicator (KPI) of the room - Number of adverse events | Number of adverse events detected in the HoSmartAI room. | Every month up to 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Box and Blocks Test | The patient has to carry as much cubes as possible, one by one, from a box to another one in one minute. The test is performed with both hands. | Change from Baseline Box and Blocks Test at 3 weeks |
| Reaching Performance Scale |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Giorgia Pregnolato | Contact | +39 0412207 | 214 | giorgia.pregnolato@hsancamillo.it |
| Valeria Campanini | Contact | +39 0412207 | 428 | valeria.campanini@hsancamillo.it |
| Name | Affiliation | Role |
|---|---|---|
| Giorgia Pregnolato | IRCCS San Camillo Hospital | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| IRCCS San Camillo Hospital | Recruiting | Venice-Lido | Venice | 30126 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30269804 | Background | Molteni F, Gasperini G, Cannaviello G, Guanziroli E. Exoskeleton and End-Effector Robots for Upper and Lower Limbs Rehabilitation: Narrative Review. PM R. 2018 Sep;10(9 Suppl 2):S174-S188. doi: 10.1016/j.pmrj.2018.06.005. | |
| 26847320 | Background | Orihuela-Espina F, Roldan GF, Sanchez-Villavicencio I, Palafox L, Leder R, Sucar LE, Hernandez-Franco J. Robot training for hand motor recovery in subacute stroke patients: A randomized controlled trial. J Hand Ther. 2016 Jan-Mar;29(1):51-7; quiz 57. doi: 10.1016/j.jht.2015.11.006. Epub 2015 Nov 26. |
| Label | URL |
|---|---|
| The link of the Pilot #3 refers to the HoSmartAI projects | View source |
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| ID | Term |
|---|---|
| D009422 | Nervous System Diseases |
| D000068079 | Motor Disorders |
| ID | Term |
|---|---|
| D001523 | Mental Disorders |
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Longitudinal Pilot study
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Reaching Performance Scale assesses the ability of subjects to reach an object (acone). The cone is placed at both 4-cm (close) and 30-cm (far) distance from the subject. The subject is asked to reach and grab the cone if possible. The assessor valuates the quality of reaching instead of the grip strength. The minimum value is0 points, which corresponds to incapacity of any ability of reaching an object. The maximum value is 36 points, which corresponds to the preservation of the ability to reach an object.
| Change from Baseline Reaching Performance Scale at 3 weeks |
| Nine Hole Pegboard Test | Nine Hole Pegboard Test measures the dexterity of the hand. Patient should insert 9 pins in the board. The number of pins inserted in 50 sec are registered or if the patient inserted 9 pins, then the time is registered. | Change from Baseline Nine Hole Pegboard Test at 3 weeks |
| Berg balance scale (BBS) | BBS is a 14-item objective measure that assesses static balance and fall risk in adults. The minimum value is 0 (i.e., no stability and high fall risk) and the maximum value is 56 (i.e., no balance disorder and no fall risk). | Change from Baseline BBS at 3 weeks |
| 10 Meter Walk Test (10MWT) | The 10MWT assesses walking speed in meters per second over a short duration.The individual is instructed to walk a set distance (6 meters, 10 meters, etc). Time is measured while the individual walks the set distance (often the individual is given space to accelerate to his/her preferred walking speed (this distance is not included when determining speed). The distance covered is divided by the time it took the individual to walk that distance.Assistive devices may be used but must be documented from test to test.If a patient requires assistance, only the minimum amount of assistance required for a patient to complete the task should be provided. The level of assistance documented, however, should reflect the greatest amount of assistance provided during the test. | Change from Baseline 10MWT at 3 weeks |
| Functional Ambulation Categories (FAC) | FAC is a functional walking test that evaluates ambulation ability. This 6-point scale assesses ambulation status by determining how much human support the patient requires when walking, regardless of whether or not they use a personal assistive device. The minimum value is 0 (i.e., patient cannot walk) and the maximum value is 6 (i.e., patient can walk independently anywhere). | Change from Baseline FAC at 3 weeks |
| Trunk Control Test (TCT) | The TCT measures four simple aspects of trunk movement :rolling to weak side,rolling to strong side
| Change from Baseline TCT at 3 weeks |
| EuroQol questionnaire (EQ-5D) | EQ-5D is a self-report survey that measures quality of life across 5 domains: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension is scored on a 5-level severity ranking that ranges from "no problems" through "extreme problems." | Change from Baseline EQ-5D at 3 weeks |
| System Usability Scale (SUS) | SUS is a widely used questionnaire for assessing the perceived usability of a system or product.The SUS consists of a 10-item questionnaire where users rate their agreement or disagreement with a series of statements regarding the usability of a system. The minimum value is 0 (i.e., the system is not usable) and the maximum value is 100 (i.e., the system is absolutely usable). | Change from Baseline SUS at 3 weeks |
| Short Form Patient Satisfaction Questionnaire (PSQ-18) | he Patient Satisfaction Questionnaire Short Form (PSQ-18) is a validated tool used to measure patient satisfaction with medical care. It is a shorter version of the 50-item Patient Satisfaction Questionnaire III (PSQ-III) 1. The PSQ-18 contains 18 items that measure seven dimensions of satisfaction with medical care: general satisfaction, technical quality, interpersonal manner, communication, financial aspects, time spent with doctor, and accessibility and convenience | Change from Baseline PSQ-18 at 3 weeks |
| User Experience Questionnaire (UEQ) | UEQ is a widely used questionnaire to measure the subjective impression of users towards the user experience of products. The UEQ is a semantic differential with 26 items that are grouped into six scales (Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, and Novelty). Each scale represents a distinct UX quality aspect. The minimum value is 0 (i.e., the worst user experience) and the maximum value is 100 (i.e., the best user experience). | Change from Baseline UEQ at 3 weeks |
| Number of falls | The patients has to count the number of falls in the last year (i.e., 12 months) and in the last 3 weeks. | Require multiple time points before the training to obtain the value (i.e.,12 months, 3 weeks) |
| 33337294 | Background | Latella D, Maggio MG, Maresca G, Andaloro A, Anchesi S, Pajno V, De Luca R, Di Lorenzo G, Manuli A, Calabro RS. Effects of domotics on cognitive, social and personal functioning in patients with Parkinson's disease: A pilot study. Assist Technol. 2022 Jul 4;34(4):423-428. doi: 10.1080/10400435.2020.1846095. Epub 2021 Apr 6. |
| 31501039 | Background | Maggio MG, Maresca G, Russo M, Stagnitti MC, Anchesi S, Casella C, Zichitella C, Manuli A, De Cola MC, De Luca R, Calabro RS. Effects of domotics on cognitive, social and personal functioning in patients with chronic stroke: A pilot study. Disabil Health J. 2020 Jan;13(1):100838. doi: 10.1016/j.dhjo.2019.100838. Epub 2019 Sep 4. |
| 24956581 | Background | Wolbring G, Lashewicz B. Home care technology through an ability expectation lens. J Med Internet Res. 2014 Jun 20;16(6):e155. doi: 10.2196/jmir.3135. |
| 37012673 | Background | Cleland J, Hutchinson C, Williams PAH, Manuel K, Laver K. A scoping review to explore the health, social and economic outcomes of home automation for people with disability. Disabil Rehabil Assist Technol. 2024 May;19(4):1446-1453. doi: 10.1080/17483107.2023.2196308. Epub 2023 Apr 3. |