DoMoMEA: a Home-Based Telerehabilitation System for Stroke Patients

Zedda, Andrea; Gusai, E.; Caruso, Marco; Bertuletti, Stefano; Baldazzi, Giulia; Spanu, S.; Riboni, Daniele; Pibiri, A.; Monticone, Marco; Cereatti, Andrea; Pani, Danilo

doi:10.1109/embc44109.2020.9175742

Cited by 13 publications

(7 citation statements)

References 7 publications

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“…Depending on the specific application, the computation time required by each SFA to compute the orientation may be crucial. In those applications providing feedback to the patient such as the tele-rehabilitation and neuroprosthesis systems, the “near” real-time estimation is a fundamental requirement [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All

Caruso

Sabatini

Laidig

et al. 2021

Sensors

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The orientation of a magneto and inertial measurement unit (MIMU) is estimated by means of sensor fusion algorithms (SFAs) thus enabling human motion tracking. However, despite several SFAs implementations proposed over the last decades, there is still a lack of consensus about the best performing SFAs and their accuracy. As suggested by recent literature, the filter parameters play a central role in determining the orientation errors. The aim of this work is to analyze the accuracy of ten SFAs while running under the best possible conditions (i.e., their parameter values are set using the orientation reference) in nine experimental scenarios including three rotation rates and three commercial products. The main finding is that parameter values must be specific for each SFA according to the experimental scenario to avoid errors comparable to those obtained when the default parameter values are used. Overall, when optimally tuned, no statistically significant differences are observed among the different SFAs in all tested experimental scenarios and the absolute errors are included between 3.8 deg and 7.1 deg. Increasing the rotation rate generally leads to a significant performance worsening. Errors are also influenced by the MIMU commercial model. SFA MATLAB implementations have been made available online.

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Section: Discussionmentioning

confidence: 99%

Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All

Caruso

Sabatini

Laidig

et al. 2021

Sensors

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“…Most current wearable systems estimate kinematics offline due to the significant number of processing steps and computation requirements. Computing kinematics in real-time is necessary for providing rapid results or diagnoses as well as applications that require feedback to the wearer, such as correcting a rehabilitation exercise [9] or improving an athletic maneuver [10].…”

Section: Introductionmentioning

confidence: 99%

An Open-Source and Wearable System for Measuring 3D Human Motion in Real-Time

Slade

Habib

Hicks

et al. 2022

IEEE Trans. Biomed. Eng.

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Objective: Analyzing human motion is essential for diagnosing movement disorders and guiding rehabilitation for conditions like osteoarthritis, stroke, and Parkinson s disease. Optical motion capture systems are the standard for estimating kinematics, but the equipment is expensive and requires a predefined space. While wearable sensor systems can estimate kinematics in any environment, existing systems are generally less accurate than optical motion capture. Many wearable sensor systems require a computer in close proximity and use proprietary software, limiting experimental reproducibility. Methods: Here, we present OpenSenseRT, an open-source and wearable system that estimates upper and lower extremity kinematics in real time by using inertial measurement units and a portable microcontroller. Results: We compared the OpenSenseRT system to optical motion capture and found an average RMSE of 4.4 degrees across 5 lower-limb joint angles during three minutes of walking and an average RMSE of 5.6 degrees across 8 upper extremity joint angles during a Fugl-Meyer task. The open-source software and hardware are scalable, tracking 1 to 14 body segments, with one sensor per segment. A musculoskeletal model and inverse kinematics solver estimate Kinematics in real-time. The computation frequency depends on the number of tracked segments, but is sufficient for real-time measurement for many tasks of interest; for example, the system can track 7 segments at 30 Hz in real-time. The system uses off-the-shelf parts costing approximately $100 USD plus $20 for each tracked segment. Significance: The OpenSenseRT system is validated against optical motion capture, low-cost, and simple to replicate, enabling movement analysis in clinics, homes, and freeliving settings.

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“…Moreover, in the study of (Zedda et al, 2020) the exergame is implemented in Unity 3D and is supported by a web application accessible from anywhere by medical staff and patients, allowing constant monitoring of rehabilitation progress.…”

Section: Web Based Frameworkmentioning

confidence: 99%

Home-based telerehabilitation: A review of remote therapy frameworks

Miguel

Sá

Souza

et al. 2021

RSD

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Remote therapy frameworks play the main role in home-based telerehabilitation. These remote therapies are exergames that help in the physical and cognitive rehabilitation of the patient. The objective of this review is to present the frameworks of home-based therapies using exergames and to identify the points that can be improved in the development of future systems. To carry out this research, the criteria of the PRISMA were adopted. Literature searches were conducted up to April 2021 in the Web of Sicence, Pubmed, Cochrane, Embase and Scopus databases. The search query was: (("game*" OR "exergame*") AND ("rehabilitation") AND ("remote" OR "telerehabilitation" OR "telemedicine")). We have selected a total of fourteen studies. We found five types of frameworks: Client-Server, Web-Based, Layers, Cloud Based and Multi users. We identified that it may be advantageous to mix the features of these frameworks to have a cheaper home-based system and prevent the patient from having to purchase more powerful computers. In addition, there are some challenges that need to be studied that will also help reduce costs for the patient: 1) Reduce the need for high processing of exergames on the patient's computer; 2) Prevent the patient from having to purchase expensive external devices for motion tracking.

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DoMoMEA: a Home-Based Telerehabilitation System for Stroke Patients

Cited by 13 publications

References 7 publications

Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All

Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All

An Open-Source and Wearable System for Measuring 3D Human Motion in Real-Time

Home-based telerehabilitation: A review of remote therapy frameworks

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