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Validation of a Quantitative Single-Subject Based Evaluation for Rehabilitation-Induced Improvement Assessment

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Abstract

The foreseen outcome of a rehabilitation treatment is a stable improvement on the functional outcomes, which can be longitudinally assessed through multiple measures to help clinicians in functional evaluation. In this study, we propose an automatic comprehensive method of combining multiple measures in order to assess a functional improvement. As test-bed, a functional electrical stimulation based treatment for foot drop correction performed with chronic post-stroke participants is presented. Patients were assessed on five relevant outcome measures before, after intervention, and at a follow-up time-point. A novel algorithm based on variables minimum detectable change is proposed and implemented in a custom-made software, combining the outcome measures to obtain a unique parameter: capacity score. The difference between capacity scores at different timing is thresholded to obtain improvement evaluation. Ten clinicians evaluated patients on the Improvement Clinical Global Impression scale. Eleven patients underwent the treatment, and five resulted to achieve a stable functional improvement, as assessed by the proposed algorithm. A statistically significant agreement between intra-clinicians and algorithm-clinicians evaluations was demonstrated. The proposed method evaluates functional improvement on a single-subject yes/no base by merging different measures (e.g., kinematic, muscular) and it is validated against clinical evaluation.

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Abbreviations

EMG:

Electromyography

EV:

Endurance velocity

CGI-I:

Clinical Global Impression scale for Improvement

CS:

Capacity score

GV:

Gait velocity

ICC:

Interclass correlation coefficient

IS:

Improvement score

MAS:

Modified Ashworth Scale

MDC:

Minimum detectable change

MRC index:

Medical Research Council index

FD:

Foot drop

FES:

Functional electrical stimulation

PSL:

Paretic step length

SEM:

Standard error of measurement

TAAI:

Tibialis anterior activation

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Acknowledgments

This work was made possible thanks to the patients that agreed to participate to the project.

Conflict of interest

The authors report no declaration of interests.

Author information

Authors and Affiliations

  1. NearLab - Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via G. Colombo 40, 20133, Milan, Italy

    Marta Gandolla, Giancarlo Ferrigno & Alessandra Pedrocchi

  2. Villa Beretta Rehabilitation Center, Valduce Hospital, Via N. Sauro 17, 23845, Costa Masnaga, LC, Italy

    Franco Molteni & Eleonora Guanziroli

  3. Sobell Department of Movement Neuroscience, UCL Institute of Neurology, 33 Queen Square, London, UK

    Nick S. Ward

Authors
  1. Marta Gandolla
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  2. Franco Molteni
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  3. Nick S. Ward
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  4. Eleonora Guanziroli
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  5. Giancarlo Ferrigno
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  6. Alessandra Pedrocchi
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Corresponding author

Correspondence to Marta Gandolla.

Additional information

Associate Editor Amit Gefen oversaw the review of this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 24404 kb)

Supplemental file 2

Carryover effect evaluation software.exe. This executable file contains a custom-made software developed in Matlab environment (MatlabR2010b) that implements the proposed algorithm and allows carryover effect evaluation. Before to run the application verify the MATLAB Compiler Runtime (MCR) is installed and ensure you have installed version 8.3 (R2014a). If the MCR is not installed, or you have a different version, freely download it from the MathWorks Web site by navigating to—http://www.mathworks.com/products/compiler/mcr/index.html (EXE 552 kb)

Supplemental file 3

Readme.pdf. This pdf file contains the basic information and a short guide for the carryover effect evaluation software use (PDF 323 kb)

Supplemental file 4

Reference values Gandolla et al.xls. This excel file contains the reference value used in the paper for the outcome measures described (XLSX 8 kb)

Supplemental file 5

Template_reference.xls. Template for reference values file preparation (XLSX 8 kb)

Supplemental file 6

Template_patients.xls. Template for patients values file preparation (XLSX 8 kb)

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Gandolla, M., Molteni, F., Ward, N.S. et al. Validation of a Quantitative Single-Subject Based Evaluation for Rehabilitation-Induced Improvement Assessment. Ann Biomed Eng 43, 2686–2698 (2015). https://doi.org/10.1007/s10439-015-1317-4

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  • DOI: https://doi.org/10.1007/s10439-015-1317-4

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