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8. Effect of using of a lower-extremity exoskeleton on disability of people with multiple sclerosis.

Author

McGibbon, Chris, Sexton, Andrew, Gryfe, Pearl, Dutta, Tilak, Jayaraman, Arun, Deems-Dluhy, Susan, Novak, Alison, Fabara, Eric, Adans-Dester, Catherine, and Bonato, Paolo

Subjects
MULTIPLE sclerosis, INFERENTIAL statistics, ROBOTIC exoskeletons, CONFIDENCE, ANALYSIS of variance, CONFIDENCE intervals, SELF-evaluation, LEG, RANDOMIZED controlled trials, T-test (Statistics), RESEARCH funding, DESCRIPTIVE statistics, CHI-squared test, INTRACLASS correlation, QUESTIONNAIRES, PEOPLE with disabilities, STATISTICAL sampling, DATA analysis software, CROSSOVER trials, FATIGUE (Physiology)
Abstract

Although ongoing exercise is known to reduce disability in people with multiple sclerosis (MS), participation in lower-extremity exercise programs can be limited by their existing mobility impairments. Lower-extremity exoskeletons could address this problem by facilitating home and community locomotion and enhancing exercise capability but little data is available on the potential of this technology for reducing disability of people with MS. We evaluated the Keeogo™ exoskeleton for people with MS using an open-label randomised cross-over design. The trial design allowed us to quantify rehabilitation effects (tested without device) and training effects (tested with device) using functional outcomes: 6-minute walk test (6MWT), timed stair test (TST), and timed up-and-go (TUG). Baseline and post-study self-report instruments included Medical Outcomes Survey Short Form-36 (SF36), MS Walking Scale (MSWS), and others. Amount of home use was documented by daily activity log. Partial correlation analysis was used to explore the relationships between changes in functional outcomes and self-report disability, controlling for amount of home use of the device. Twenty-nine participants with MS completed the trial. Change scores for MSWS, SF36 physical function and SF36 emotional well-being correlated positively with changes in 6MWT which was explained by amount of home use. The benefits in physical functioning and emotional well-being from using the exoskeleton at home were linked to amount of device usage. Low-profile robotic exoskeletons could be used to deliver facilitated exercise while assisting with locomotor activities of daily living, such as walking and stair climbing in the home and community environment. Exoskeletons for home use may have the potential to benefit people with MS in terms of physical functioning and emotional well-being. The benefits in physical functioning and emotional well-being appeared to be linked to amount of usage. Exoskeletons might be useful for delivering facilitated exercise while assisting with walking and stair climbing in the home. [ABSTRACT FROM AUTHOR]

Published
2023
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9. Voice Biomarkers of Recovery From Acute Respiratory Illness

Author

Tracey, Brian, primary, Patel, Shyamal, additional, Zhang, Yao, additional, Chappie, Kara, additional, Volfson, Dmitri, additional, Parisi, Federico, additional, Adans-Dester, Catherine, additional, Bertacchi, Francesco, additional, Bonato, Paolo, additional, and Wacnik, Paul, additional

Published
2022
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10. Evaluation of a lower-extremity robotic exoskeleton for people with knee osteoarthritis.

Author

McGibbon, Chris, Sexton, Andrew, Jayaraman, Arun, Deems-Dluhy, Susan, Fabara, Eric, Adans-Dester, Catherine, Bonato, Paolo, Marquis, Francois, Turmel, Sylvie, and Belzile, Etienne

Abstract

A multi-site study was conducted to evaluate the efficacy of the Keeogo™ exoskeleton as a mobility assist device for use in the clinic and at home in people with knee osteoarthritis (KOA). Twenty-four participants were randomized in a two-stage cross-over design that evaluated the immediate effects of using the exoskeleton in the clinic and the cumulative effects of training and home use. Immediate effects were quantified by comparing 1) physical performance with|without (W|WO) the device during a battery of mobility tests, and 2) physical activity levels at home (actigraphy) for one month, two weeks W|WO the device. Cumulative effects were quantified as change in physical performance W and WO over time. WOMAC and other self-report scales were measured and usability assessed. There were no immediate effects on physical performance or physical activity at home; however, there were cumulative effects as indicated by improved stair time (p =.001) as well as improved WOMAC pain (p =.004) and function (p =.003). There was a direct relationship between improved physical function and improved WOMAC pain (r = −.677, p <.001) and stiffness (r =.537, p =.007). Weight and battery life were identified as important to usability. A full-scale RCT with more participants, longer study period, and better usage monitoring is warranted. [ABSTRACT FROM AUTHOR]

Published
2022
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13. Additional file 1 of Can kinematic parameters of 3D reach-to-target movements be used as a proxy for clinical outcome measures in chronic stroke rehabilitation? An exploratory study

Author

Adans-Dester, Catherine, Fasoli, Susan E., Fabara, Eric, Menard, Nicolas, Fox, Annie B., Severini, Giacomo, and Bonato, Paolo

Abstract

Additional file 1: Figure S1A. Variance observed across targets in the kinematic variables of efficiency in the non-paretic and paretic arm. Figure S1B. Variance observed across targets in the kinematic variables of speed and planning in the non-paretic and paretic arm. Figure S1C. Variance observed across targets in the kinematic variables of smoothness in the non-paretic and paretic arm. Figure S1D. Variance observed across targets in the kinematic variables of trunk posture in the non-paretic and paretic arm. Figure S1E. Variance observed across targets in the kinematic variables of arm posture in the non-paretic and paretic arm.

Published
2020
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14. Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Author

Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Adans-Dester, Catherine P., Bamberg, Stacy, Bertacchi, Francesco P., Caulfield, Brian, Chappie, Kara, Demarchi, Danilo, Erb, M. Kelley, Estrada, Juan, Fabara, Eric E., Freni, Michael, Friedl, Karl E., Ghaffari, Roozbeh, Gill, Geoffrey, Greenberg, Mark S., Hoyt, Reed W., Jovanov, Emil, Kanzler, Christoph M., Katabi, Dina, Kernan, Meredith, Kigin, Colleen, Lee, Sunghoon I., Leonhardt, Steffen, Lovell, Nigel H., Mantilla, Jose, McCoy, Thomas H., Luo, Nell Meosky, Miller, Glenn A., Moore, John, O'Keeffe, Derek, Palmer, Jeffrey, Parisi, Federico, Patel, Shyamal, Po, Jack, Pugliese, Benito L., Quatieri, Thomas, Rahman, Tauhidur, Ramasarma, Nathan, Rogers, John A., Ruiz-Esparza, Guillermo U., Sapienza, Stefano, Schiurring, Gregory, Schwamm, Lee, Shafiee, Hadi, Kelly Silacci, Sara, Sims, Nathaniel M, Talkar, Tanya, Tharion, William J., Toombs, James A., Uschnig, Christopher, Vergara-Diaz, Gloria P., Wacnik, Paul, Wang, May D., Welch, James, Williamson, Lina, Zafonte, Ross, Zai, Adrian, Zhang, Yuan-Ting, Tearney, Guillermo J., Ahmad, Rushdy, Walt, David R., Bonato, Paolo, Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Adans-Dester, Catherine P., Bamberg, Stacy, Bertacchi, Francesco P., Caulfield, Brian, Chappie, Kara, Demarchi, Danilo, Erb, M. Kelley, Estrada, Juan, Fabara, Eric E., Freni, Michael, Friedl, Karl E., Ghaffari, Roozbeh, Gill, Geoffrey, Greenberg, Mark S., Hoyt, Reed W., Jovanov, Emil, Kanzler, Christoph M., Katabi, Dina, Kernan, Meredith, Kigin, Colleen, Lee, Sunghoon I., Leonhardt, Steffen, Lovell, Nigel H., Mantilla, Jose, McCoy, Thomas H., Luo, Nell Meosky, Miller, Glenn A., Moore, John, O'Keeffe, Derek, Palmer, Jeffrey, Parisi, Federico, Patel, Shyamal, Po, Jack, Pugliese, Benito L., Quatieri, Thomas, Rahman, Tauhidur, Ramasarma, Nathan, Rogers, John A., Ruiz-Esparza, Guillermo U., Sapienza, Stefano, Schiurring, Gregory, Schwamm, Lee, Shafiee, Hadi, Kelly Silacci, Sara, Sims, Nathaniel M, Talkar, Tanya, Tharion, William J., Toombs, James A., Uschnig, Christopher, Vergara-Diaz, Gloria P., Wacnik, Paul, Wang, May D., Welch, James, Williamson, Lina, Zafonte, Ross, Zai, Adrian, Zhang, Yuan-Ting, Tearney, Guillermo J., Ahmad, Rushdy, Walt, David R., and Bonato, Paolo

Abstract

Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing.

Published
2020

16. Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Author

Adans-Dester, Catherine P., primary, Bamberg, Stacy, additional, Bertacchi, Francesco P., additional, Caulfield, Brian, additional, Chappie, Kara, additional, Demarchi, Danilo, additional, Erb, M. Kelley, additional, Estrada, Juan, additional, Fabara, Eric E., additional, Freni, Michael, additional, Friedl, Karl E., additional, Ghaffari, Roozbeh, additional, Gill, Geoffrey, additional, Greenberg, Mark S., additional, Hoyt, Reed W., additional, Jovanov, Emil, additional, Kanzler, Christoph M., additional, Katabi, Dina, additional, Kernan, Meredith, additional, Kigin, Colleen, additional, Lee, Sunghoon I., additional, Leonhardt, Steffen, additional, Lovell, Nigel H., additional, Mantilla, Jose, additional, McCoy, Thomas H., additional, Luo, Nell Meosky, additional, Miller, Glenn A., additional, Moore, John, additional, O'Keeffe, Derek, additional, Palmer, Jeffrey, additional, Parisi, Federico, additional, Patel, Shyamal, additional, Po, Jack, additional, Pugliese, Benito L., additional, Quatieri, Thomas, additional, Rahman, Tauhidur, additional, Ramasarma, Nathan, additional, Rogers, John A., additional, Ruiz-Esparza, Guillermo U., additional, Sapienza, Stefano, additional, Schiurring, Gregory, additional, Schwamm, Lee, additional, Shafiee, Hadi, additional, Kelly Silacci, Sara, additional, Sims, Nathaniel M, additional, Talkar, Tanya, additional, Tharion, William J., additional, Toombs, James A., additional, Uschnig, Christopher, additional, Vergara-Diaz, Gloria P., additional, Wacnik, Paul, additional, Wang, May D., additional, Welch, James, additional, Williamson, Lina, additional, Zafonte, Ross, additional, Zai, Adrian, additional, Zhang, Yuan-Ting, additional, Tearney, Guillermo J., additional, Ahmad, Rushdy, additional, Walt, David R., additional, and Bonato, Paolo, additional

Published
2020
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28. Estimating Clinical Scores From Wearable Sensor Data In Stroke Survivors

Author

Meagher, Claire, primary, Sapienza, Stefano, additional, Adans-Dester, Catherine, additional, O’Brien, Anne, additional, Patel, Shyamal, additional, Vergara-Diaz, Gloria, additional, Demarchi, Danilo, additional, Lee, Sunghoon, additional, Hughes, Ann-Marie, additional, Black-Schaffer, Randie, additional, Burridge, Jane, additional, Zafonte, Ross, additional, and Bonato, Paolo, additional

Published
2017
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32. Using a Minimum Set of Wearable Sensors to Assess Quality of Movement in Stroke Survivors

Author

Sapienza, Stefano, primary, Adans-Dester, Catherine, additional, OBrien, Anne, additional, Vergara-Diaz, Gloria, additional, Lee, Sunghoon, additional, Patel, Shyamal, additional, Black-Schaffer, Randie, additional, Zafonte, Ross, additional, Bonato, Paolo, additional, Meagher, Claire, additional, Hughes, Ann-Marie, additional, Burridge, Jane, additional, and Demarchi, Danilo, additional

Published
2017
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39. Evaluation of the Keeogo exoskeleton for assisting ambulatory activities in people with multiple sclerosis: an open-label, randomized, cross-over trial.

Author

Sexton, Andrew, McGibbon, Chris A., Jayaraman, Arun, Deems-Dluhy, Susan, Gryfe, Pearl, Novak, Alison, Dutta, Tilak, Fabara, Eric, Adans-Dester, Catherine, and Bonato, Paolo

Subjects
MULTIPLE sclerosis, NEUROLOGICAL disorders, ORTHOPEDIC apparatus, PHYSICAL therapy for multiple sclerosis, PHYSICAL activity
Abstract

Background: Although physical activity and exercise is known to benefit people with multiple sclerosis (MS), the ability of these individuals to participate in such interventions is difficult due to the mobility impairments caused by the disease. Keeogo is a lower-extremity powered exoskeleton that may be a potential solution for enabling people with MS to benefit from physical activity and exercise.Methods: An open-label, randomized, cross-over trial was used to examine the immediate performance effects when using the device, and the potential benefits of using the device in a home setting for 2 weeks. Clinical performance tests with and without the device included the 6 min walk test, timed up and go test and the 10-step stair test (up and down). An activity monitor was also used to measure physical activity at home, and a patient-reported questionnaire was used to determine the amount and extent of home use. Generalized linear models were used to test for trial effects, and correlation analysis used to examine relationships between trial effects and usage.Results: Twenty-nine patients with MS participated. All measures showed small decrements in performance while wearing the device compared to not wearing the device. However, significant improvements in unassisted (Rehab effect) performance were found after using the device at home for 2 weeks, compared to 2 weeks at home without the device, and participants improved their ability to use the device over the trial period (Training effect). Rehab and Training effects were related to the self-reported extent that participants used Keeogo at home.Conclusions: Keeogo appears to deliver an exercise-mediated benefit to individuals with MS that improved their unassisted gait endurance and stair climbing ability. Keeogo might be a useful tool for delivering physical activity interventions to individuals with mobility impairment due to MS.Trial Registration: ClinicalTrials.gov : NCT02904382 . Registered 19 September 2016 - Retrospectively registered. [ABSTRACT FROM AUTHOR]

Published
2018
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