Our Publications

Recent Publications

  1. M. Johnson, “Rehabilitation Robotics Can Help Bridge Gaps in Stroke Rehabilitation Care,” presented at the 2022 Annual Meeting, Feb. 2022. Accessed: Feb. 21, 2022. [Online]. Available: https://aaas.confex.com/aaas/2022/meetingapp.cgi/Paper/29349
  2. C. Mucchiani, P. Cacchione, M. Johnson, R. Mead, and M. Yim, “Deployment of a Socially Assistive Robot for Assessment of COVID-19 Symptoms and Exposure at an Elder Care Setting,” in 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 2021, pp. 1189–1195. doi: 10.1109/RO-MAN50785.2021.9515551.
  3. L. A. Prosser et al., “Infants at risk for physical disability may be identified by measures of postural control in supine,” Pediatric Research, pp. 1–7, 2021.
  4. M. J. Sobrepera, V. G. Lee, and M. J. Johnson, “The design of Lil’Flo, a socially assistive robot for upper extremity motor assessment and rehabilitation in the community via telepresence,” Journal of Rehabilitation and Assistive Technologies Engineering, vol. 8, p. 20556683211001804, 2021, doi: 10.1177/20556683211001805.
  5. M. J. Sobrepera, V. G. Lee, S. Garg, R. Mendonca, and M. J. Johnson, “Perceived usefulness of a social robot augmented telehealth platform by therapists in the United States,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 2946–2953, 2021, doi: 10.1109/LRA.2021.3062349.
  6. K. D. Bui, C. A. Wamsley, F. S. Shofer, D. L. Kolson, and M. J. Johnson, “Robot-based assessment of HIV-related motor and cognitive impairment for neurorehabilitation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 29, pp. 576–586, 2021, doi: 10.1109/TNSRE.2021.3056908.
  7. N. T. Fitter, M. Mohan, K. J. Kuchenbecker, and M. J. Johnson, “Exercising with Baxter: preliminary support for assistive social-physical human-robot interaction,” Journal of neuroengineering and rehabilitation, vol. 17, no. 1, pp. 1–22, 2020, doi: 10.1186/s12984-020-0642-5.
  8. V. C. Espinoza Bernal, S. V. Hiremath, B. Wolf, B. Riley, R. J. Mendonca, and M. J. Johnson, “Classifying and tracking rehabilitation interventions through machine-learning algorithms in individuals with stroke,” Journal of Rehabilitation and Assistive Technologies Engineering, vol. 8, p. 20556683211044640, 2021, doi: 10.1177/20556683211044640.
  9. R. Rai, M. J. Johnson, and S. Sharma, “Robotic physical therapy systems and data analysis of user interactions.” Google Patents, Aug. 17, 2021.
  10. S. Hu, R. Mendonca, M. J. Johnson, and K. J. Kuchenbecker, “Robotics for Occupational Therapy: Learning Upper-Limb Exercises From Demonstrations,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 7781–7788, 2021, doi: 10.1109/LRA.2021.3098945.
  11. A. Stewart-Height, D. E. Koditschek, and M. J. Johnson, “Reimagining robotic walkers for real-world outdoor play environments with insights from legged robots: a scoping review,” Disability and Rehabilitation: Assistive Technology, pp. 1–21, 2021, doi: 10.1080/17483107.2021.1926563.
  12. A. Demofonti, G. Carpino, L. Zollo, and M. J. Johnson, “Affordable robotics for upper limb stroke rehabilitation in developing countries: a systematic review,” IEEE Transactions on Medical Robotics and Bionics, 2021, doi: 10.1109/TMRB.2021.3054462.
  13. T. Hirsch et al., “A First Step Toward the Operationalization of the Learned Non-Use Phenomenon: A Delphi Study,” Neurorehabilitation and Neural Repair, vol. 35, no. 5, pp. 383–392, 2021, doi: 10.1177/1545968321999064.
  14. S. Lysenko, N. Seethapathi, L. Prosser, K. Kording, and M. J. Johnson, “Towards Automated Emotion Classification of Atypically and Typically Developing Infants,” in 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 2020, pp. 503–508. doi: 10.1109/BioRob49111.2020.9224271.
  15. C. Chambers et al., “Computer vision to automatically assess infant neuromotor risk,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 11, pp. 2431–2442, 2020, doi: 10.1109/TNSRE.2020.3029121.
  16. C. Mucchiani, P. Cacchione, R. Mead, M. J. Johnson, and M. Yim, “On New Research Guidelines for the Deployment of Socially Assistive Robots for Elder Care Amidst the COVID-19 Pandemic,” 2020.
  17. C. Mucchiani, P. Cacchione, W. Torres, M. J. Johnson, and M. Yim, “Exploring low-cost mobile manipulation for elder care within a community based setting,” Journal of Intelligent & Robotic Systems, vol. 98, no. 1, pp. 59–70, 2020, doi: 10.1007/s10846-019-01041-x.
  18. S. Gaardsmoe, M. Ovando, K. Bui, and M. J. Johnson, “Development of a low-cost balance assessment system for use in an affordable robot gym in low and middle income countries,” in 2020 IEEE 11th Latin American Symposium on Circuits & Systems (LASCAS), 2020, pp. 1–6. doi: 10.1109/LASCAS45839.2020.9069007.
  19. K. D. B. Valles, D. C. Marquez, and M. J. Johnson, “Robotic rehabilitation therapy in Chihuahua Mexico, challenges from translating a clinical research protocol to clinical practice,” in 2020 IEEE 11th Latin American Symposium on Circuits & Systems (LASCAS), 2020, pp. 1–4. doi: 10.1109/LASCAS45839.2020.9068966.
  20. F. Cordella, L. Zollo, and M. J. Johnson, “Analysis of Human Behavior for Robot Design and Control,” Applied Bionics and Biomechanics, vol. 2020. Hindawi, 2020.
  21. M. J. Johnson, K. Bui, and N. Rahimi, “Medical and Assistive Robotics in Global Health,” Handbook of Global Health, pp. 1–46, 2020.
  22. K. D. Bui and M. J. Johnson, “Objective Robot-Based Measures of Cognitive and Motor Function in Patients with Stroke and HIV,” in 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 2020, pp. 910–915. doi: 10.1109/BioRob49111.2020.9224275.
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  24. Q. Zhu, D. Sigmon, I. S. Soriano, K. Dumon, and M. J. Johnson, “Development of an Interactive Anatomical Model for Robotic TAPP Inguinal Hernia Repair Surgical Training,” in 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 2020, pp. 897–902. doi: 10.1109/BioRob49111.2020.9224270.
  25. T. Hirsch et al., “Operationalization of the learned non-use phenomenon-A Delphi study,” medRxiv, 2020.
  26. E. S. Ho, W. Torres, L. Prosser, and M. J. Johnson, “Ailu: An Affordable Sensorized Toy for Detection of Neuro and Motor Delays in Infants,” in 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), 2019, pp. 994–999. doi: 10.1109/ICORR.2019.8779523.
  27. W. S. Wang, R. Mendonca, K. Kording, M. Avery, and M. J. Johnson, “Towards Data-Driven Autonomous Robot-Assisted Physical Rehabilitation Therapy,” in 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), 2019, pp. 34–39. doi: 10.1109/ICORR.2019.8779555.
  28. M. J. Sobrepera, E. Kina, and M. J. Johnson, “Designing and evaluating the face of lil’Flo: an affordable social rehabilitation robot,” in 2019 IEEE 16th international conference on rehabilitation robotics (ICORR), 2019, pp. 748–753. doi: 10.1109/ICORR.2019.8779416.
  29. K. D. Bui and M. J. Johnson, “Robot-based measures of upper limb cognitive-motor interference across the HIV-stroke spectrum,” in 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), 2019, pp. 530–535. doi: 10.1109/ICORR.2019.8779418.
  30. C. Mucchiani, P. Cacchione, R. Mead, M. Johnson, and M. Yim, “Preliminary Hardware and System Design Investigation for an Affordable and Mobile Assistive Robot for Elderly Care,” 2019.
  31. A. D. Goodworth, M. J. Johnson, and M. B. Popovic, “Physical Therapy and Rehabilitation,” Biomechatronics, p. 333, 2019, doi: 10.1016/B978-0-12-812939-5.00012-4.
  32. M. J. Johnson, M. J. Sobrepera, E. Kina, and R. Mendonca, “Design of an affordable socially assistive robot for remote health and function monitoring and prognostication,” International Journal of Prognostics and Health Management, vol. 10, no. 3, 2019.
  33. K. D. Bui and M. J. Johnson, “Designing robot-assisted neurorehabilitation strategies for people with both HIV and stroke,” Journal of neuroengineering and rehabilitation, vol. 15, no. 1, pp. 1–15, 2018, doi: 10.1186/s12984-018-0418-3.
  34. R. Mendonca and M. Johnson, “Quantifying Therapist–Patient Roles Using Video Analysis During Occupation-Based Therapy,” The American Journal of Occupational Therapy, vol. 72, no. 4_Supplement_1, pp. 7211500013p1-7211500013p1, 2018, doi: 10.5014/ajot.2018.72S1-PO2008.
  35. Ho ES, Torres W, Prosser L, Johnson MJ. Ailu: An Affordable Sensorized Toy for Detection of Neuro and Motor Delays in Infants. IEEE Int Conf Rehabil Robot. 2019;2019:994-999. doi:10.1109/ICORR.2019.8779523
  36. Kather C, Lima K, Torres W, Johnson M. Distinguishing Atypical Infant Behavior Using Elementary Kinetic Classifications. Conference: Rehabilitation Engineering Society of Korea (RESKO) 2019; 2018.
  37. C. Mucchiani, W. O. Torres, D. Edgar, M. J. Johnson, P. Z. Cacchione, and M. Yim, “Development and deployment of a mobile manipulator for assisting and entertaining elders living in supportive apartment living facilities,” in 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2018, pp. 121–128. doi: 10.1109/ROMAN.2018.8525826.
  38. K. D. Bui and M. J. Johnson, “Developing Robot-Based Cognitive and Motor Tasks for People Living with Both HIV and Stroke* This work was made possible through core services and support from the University of of Pennsylvania’s Center for AIDS Research (CFAR), an NIH-funded program (P30 AI 045008), the Center for Biomedical Image Computing and Analytics, and the Departments of Bioengineering and Physical Medicine and Rehabilitation.,” in 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), 2018, pp. 31–36. doi: 10.1109/BIOROB.2018.8487670.
  39. K. D. Bui and M. J. Johnson, “Towards Robot-Based Cognitive and Motor Assessment Across the HIV-Stroke Spectrum,” in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, pp. 3618–3621. doi: 10.1109/EMBC.2018.8513091.
  40. R. O. Smith et al., “Assistive technology products: a position paper from the first global research, innovation, and education on assistive technology (GREAT) summit,” Disability and Rehabilitation: Assistive Technology, vol. 13, no. 5, pp. 473–485, 2018, doi: 10.1080/17483107.2018.1473895.
  41. N. T. Fitter, M. Mohan, K. J. Kuchenbecker, and M. J. Johnson, “Exercising with Baxter: Design and Evaluation of Assistive Social-Physical Human-Robot Interaction,” 2018.
  42. J. S. Sefcik et al., “Stakeholders’ perceptions sought to inform the development of a low-cost mobile robot for older adults: A qualitative descriptive study,” Clinical nursing research, vol. 27, no. 1, pp. 61–80, 2018, doi: 10.1177/1054773817730517.
  43. Michelle J. Johnson, Megan A. Johnson, Justine S. Sefcik, Pamela Z. Cacchione, Caio Mucchiani, Tessa Lau, and Mark Yim: Task and Design Requirements for an Affordable Mobile Service Robot for Elder Care in an All-Inclusive Care for Elders Assisted-Living Setting. International Journal of Social Robotics (2017): 1-20.
  44. Theriault, Andrew; Nagurka, Mark; Johnson, Michelle J: Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis. Transactions on Haptics. J. Edward Colgate (eds.). IEEE Computer Society In Press 2013 Notes: Special Issue: Haptics in Rehabilitation and Neural Engineering
  45. Leah R Enders, Pilwon Hur, Michelle J Johnson, Na Jin Seo: Remote vibrotactile noise improves light touch sensation in stroke survivors’ fingertips via stochastic resonance. Journal of NeuroEngineering and Rehabilitation. Biomed Central, In Press 2013.
  46. Lei Y, Johnson MJ, Wang J: Separation of visual and motor workspaces during targeted reaching results in limited generalization of visuomotor adaptation. Neurosci Lett 541: 243-7, May 2013.
  47. Xu R, Johnson MJ: Evaluating Reach and Grasp after Stroke with a Custom MR-Conditional Upper Extremity Reach and Grasp System. IEEE International Conference on Biomedical Robotics and Biomechatronics 2012 Notes: conference proceedings.
  48. Pathak Y, Johnson MJ: An Upper Limb Robot Model of Children Limb for Cerebal Palsy NeuroRehabilitation. Conf Proc IEEE Eng Med Biol Soc 2012 Notes: conference proceedings.
  49. Hui B, Hughes D, Wu H, Bhatti O, Zhao S, Johnson MJ: An MRI-Safe Algometer to Study Phantom Limb Pain. Conf Proc IEEE Eng Med Biol Soc 2012 Notes: conference proceedings.

For older publications, please visit Dr. Johnson's Google Scholar page