About

Christopher J. Hasson is an Associate Professor in the Department of Physical Therapy, Human Movement, and Rehabilitation Sciences at Bouvé College of Health Sciences, Northeastern University. His research focus is within the field of physical therapy and rehabilitation sciences, contributing to the understanding of human movement and rehabilitation practices. As a faculty member, he is involved in advancing education and research in these areas, supporting the development of future professionals in physical therapy and related disciplines.

Research topics

• Artificial Intelligence
• Computer Science
• Medicine
• Physical medicine and rehabilitation
• Psychology
• Physical therapy
• Human–computer interaction
• Neuroscience
• Physics
• Anatomy
• Surgery

Selected publications

• Robot-mediated physical Human-Human Interaction in Neurorehabilitation: a position paper

  arXiv (Cornell University) · 2025-07-23

  preprintOpen access

  Neurorehabilitation conventionally relies on the interaction between a patient and a physical therapist. Robotic systems can improve and enrich the physical feedback provided to patients after neurological injury, but they under-utilize the adaptability and clinical expertise of trained therapists. In this position paper, we advocate for a novel approach that integrates the therapist's clinical expertise and nuanced decision-making with the strength, accuracy, and repeatability of robotics: Robot-mediated physical Human-Human Interaction. This framework, which enables two individuals to physically interact through robotic devices, has been studied across diverse research groups and has recently emerged as a promising link between conventional manual therapy and rehabilitation robotics, harmonizing the strengths of both approaches. This paper presents the rationale of a multidisciplinary team-including engineers, doctors, and physical therapists-for conducting research that utilizes: a unified taxonomy to describe robot-mediated rehabilitation, a framework of interaction based on social psychology, and a technological approach that makes robotic systems seamless facilitators of natural human-human interaction.

  PublisherOA PDFDOI

• Impact of a shoulder exosuit on range of motion, endurance, and task execution in users with neurological impairments

  Wearable Technologies · 2025-01-01 · 1 citations

  articleOpen access

  The Myoshirt, an active exosuit, provides gravity compensation for the shoulders. This study evaluated the impact of the Myoshirt on range of motion (ROM), endurance, and activities of daily living (ADLs) performance through tests involving nine participants with varying levels of arm impairments and diverse pathologies. Optical motion capture was used to quantify ROM of the shoulder and elbow joints during isolated movements and functional tasks. Endurance was quantified through a timed isometric shoulder flexion task, and a battery of ADL tasks was used to measure the perceived support of the exosuit, along with changes in movement quality. Feedback and usability insights were gathered with surveys. The Myoshirt did not significantly improve ROM during isolated movements (shoulder flexion, shoulder abduction, and elbow flexion/extension), but during the reaching phase of a functional drinking task elbow extension increased significantly by 13.5% (t = 7.52, p = .002). Participants could also keep their arms elevated 78.7% longer (t = 1.942, p = .047). Patients also reported less perceived difficulty with ADLs while using the device, and a therapist reported improved execution quality. Participants who self-reported severe impairment levels tended to derive greater benefits compared to those with milder impairments. These findings highlight the potential of the Myoshirt as an assistive device, particularly for individuals with severe impairments, while emphasizing the need for further refinement.

  PublisherOA PDFDOI

• Teleoperated Gait Training: Assisting the Leg with a Robotic Arm

  Biosystems & biorobotics · 2025-01-01

  book-chapterSenior author
  PublisherDOI

• Impact of a shoulder exosuit on range of motion, endurance, and task execution in users with neurological impairments

  Universität Zürich, ZORA · 2025-01-01

  articleOpen access

  The Myoshirt, an active exosuit, provides gravity compensation for the shoulders. This study evaluated the impact of the Myoshirt on range of motion (ROM), endurance, and activities of daily living (ADLs) performance through tests involving nine participants with varying levels of arm impairments and diverse pathologies. Optical motion capture was used to quantify ROM of the shoulder and elbow joints during isolated movements and functional tasks. Endurance was quantified through a timed isometric shoulder flexion task, and a battery of ADL tasks was used to measure the perceived support of the exosuit, along with changes in movement quality. Feedback and usability insights were gathered with surveys. The Myoshirt did not significantly improve ROM during isolated movements (shoulder flexion, shoulder abduction, and elbow flexion/extension), but during the reaching phase of a functional drinking task elbow extension increased significantly by 13.5% (t = 7.52, p = .002). Participants could also keep their arms elevated 78.7% longer (t = 1.942, p = .047). Patients also reported less perceived difficulty with ADLs while using the device, and a therapist reported improved execution quality. Participants who self-reported severe impairment levels tended to derive greater benefits compared to those with milder impairments. These findings highlight the potential of the Myoshirt as an assistive device, particularly for individuals with severe impairments, while emphasizing the need for further refinement.

  PublisherDOI

• Robot-Mediated Physical Human–Human Interaction in Rehabilitation: A Position Paper

  IEEE Reviews in Biomedical Engineering · 2025-11-25 · 1 citations

  article

  Neurorehabilitation conventionally relies on the interaction between a patient and a physical therapist. Robotic systems can improve and enrich the physical feedback provided to patients after neurological injury, but they under-utilize the adaptability and clinical expertise of trained therapists. In this position paper, we advocate for a novel approach that integrates the therapist's clinical expertise and nuanced decision-making with the strength, accuracy, and repeatability of robotics: Robot-mediated physical Human-Human Interaction. This framework, which enables two individuals to physically interact through robotic devices, has been studied across diverse research groups and has recently emerged as a promising link between conventional manual therapy and rehabilitation robotics, harmonizing the strengths of both approaches. Although current findings are largely based on pilot studies and conceptual frameworks, integrating therapists' expertise with the functionalities offered by robotic systems represents a promising direction for improving rehabilitation outcomes. This paper presents the rationale of a multidisciplinary team-including engineers, doctors, and physical therapists-for conducting research that utilizes: a unified taxonomy to describe robot-mediated rehabilitation, a framework of interaction based on social psychology, and a technological approach that makes robotic systems seamless facilitators of natural human-human interaction.

  PublisherDOI

• Evaluating self-assistance during functional reach with a passive hydrostatic exoskeleton under artificial impairment

  Journal of NeuroEngineering and Rehabilitation · 2025-07-16

  articleOpen accessSenior author

  BACKGROUND: Practicing functional upper-extremity tasks with manual self-assistance may promote motor recovery and restore voluntary control to an impaired limb, reducing reliance on external aid. However, most evidence comes from studies involving tasks with limited coordinative demands. In a functional task like reaching for and lifting an object, learning to generate coordinated assistive forces with an external device may pose bilateral sensorimotor challenges that limit motor learning in the impaired limb. To address this question, we developed a passive hydrostatic exoskeleton (hEXO) that enables self-assistance and paired it with an artificial impairment paradigm using Dysfunctional Electrical Stimulation (DFES), which induces involuntary hand closure during reaching. METHODS: Twenty neurologically typical adults (26 ± 3 yrs) performed a reach-to-grasp and object lift task under challenging sensorimotor conditions: as fast as possible with their non-dominant hand while experiencing an artificial impairment induced by DFES. The stimulation functionally mimicked deficits related to a flexion synergy after neurological injury by making it difficult for participants to extend their fingers while reaching for an object. Experiment 1 assessed the short-term effects of DFES and wearing the hEXO. In Experiment 2, participants were randomly assigned to either a group that could self-assist with the hEXO (n = 10) or a control group that could not self-assist (n = 10) to investigate adaptation to self-assistance and transfer of motor performance to unassisted conditions. RESULTS: DFES created a sensorimotor challenge and increased reach-to-grasp time by about 50% during early exposure. The self-assist group improved their reach-to-grasp times faster than controls (p = 0.008), achieved comparable reaching times (p = 0.060), and had a slightly higher incidence of unsuccessful attempts (about one in 20 attempts; p < 0.001). Reach-to-grasp performance did not decline following the removal of self-assistance, indicating no performance dependency. Both groups had similar movement times and success rates in the final unassisted practice block. CONCLUSIONS: In this sample of adults with an artificial impairment, self-assistance using a passive hydrostatic exoskeleton accelerated motor performance improvements without creating a dependency on the assistance. If replicated in clinical populations, this approach may help promote upper-limb functional independence.

  PublisherOA PDFDOI

• Induced discomfort promotes executive function while walking with(out) an artificial neuromuscular impairment

  Journal of Neurophysiology · 2024-10-23 · 4 citations

  articleOpen accessSenior author

  When locomotor and cognitive tasks compete for shared neural resources, cognitive-motor interference may impair performance in both domains. To understand how impairments that cause pain or change neuromotor control impact cognition during locomotion, we gave healthy adults an uncomfortable, artificial neuromuscular impairment while they walked and completed a task dependent on ignoring distracting stimuli. We found that discomfort enhanced participants' ability to ignore distractions, providing new insight into the mediators of cognition during impaired movement.

  PublisherOA PDFDOI

• Effects Of Increasing Walking Cadence On Knee Joint Loading And Pain In Adults With Knee Osteoarthritis

  Medicine & Science in Sports & Exercise · 2024-09-16

  article

  Gait retraining is a strategy to manage altered loading patterns and pain characteristic of knee osteoarthritis (OA). Increasing cadence (steps/minute) may be a promising gait modification approach because lower preferred cadence is associated with higher knee joint loading and risk of cartilage worsening. PURPOSE: Determine the acute effects of increasing cadence on knee adduction and flexion moment peaks and impulses, and knee pain in adults with knee OA. METHODS: 25 participants with knee OA (age = 61.8 ± 7.3; 81.8% female) completed a 5-minute walk at fixed speed on an instrumented, split-belt treadmill. Baseline cadence (steps/minute) was first measured. Five, randomized experimental cadence conditions (2%, 4%, 6%, 8%, or 10% over baseline cadence) were then completed. A custom-written LabVIEW code was used to monitor and provide real-time visual feedback on cadence. Auditory cues from a metronome set to the target cadence were simultaneously provided. Participants were instructed to keep their cadence within ±1 step/minute of the target, and to walk to the beat of the metronome. Kinematics and ground reaction forces were sampled for the duration of each condition (2 minutes). Knee pain was reported on a 0-10 scale during a 1-minute rest period between each condition. Linear mixed effects models evaluated the effect of cadence on each outcome: knee adduction moment peaks and impulse, knee flexion moment peak and impulse, and knee pain. RESULTS: Increasing cadence by 2-10% did not significantly change knee adduction moment peaks or impulse. Peak knee flexion moment increased by 3-32% and knee flexion moment impulse reduced by 2-9% with increases in cadence, but these results were not significant (peak knee flexion moment, p = 0.06; knee flexion moment impulse, p = 0.05). Increasing cadence did not affect knee pain. CONCLUSIONS: In adults with knee OA, increasing preferred walking cadence by 2-10% at a fixed speed has no immediate effect on surrogate measures of knee joint loading or pain. Future research investigating cadence modification should consider feedback type and delivery and practice time, as these factors are known to influence motor performance. ACSM Foundation Doctoral Student Grant; Foundation for Physical Therapy

  PublisherDOI

• Effects of increasing walking cadence on gait biomechanics in adults with knee osteoarthritis

  Journal of Biomechanics · 2024-10-28 · 7 citations

  articleOpen access
  PublisherOA PDFDOI

• Neurorehabilitation robotics: how much control should therapists have?

  Frontiers in Human Neuroscience · 2023 · 14 citations

  1st authorCorresponding
  • Artificial Intelligence
  • Computer Science
  • Artificial Intelligence

  Robotic technologies for rehabilitating motor impairments from neurological injuries have been the focus of intensive research and capital investment for more than 30 years. However, these devices have failed to convincingly demonstrate greater restoration of patient function compared to conventional therapy. Nevertheless, robots have value in reducing the manual effort required for physical therapists to provide high-intensity, high-dose interventions. In most robotic systems, therapists remain outside the control loop to act as high-level supervisors, selecting and initiating robot control algorithms to achieve a therapeutic goal. The low-level physical interactions between the robot and the patient are handled by adaptive algorithms that can provide progressive therapy. In this perspective, we examine the physical therapist's role in the control of rehabilitation robotics and whether embedding therapists in lower-level robot control loops could enhance rehabilitation outcomes. We discuss how the features of many automated robotic systems, which can provide repeatable patterns of physical interaction, may work against the goal of driving neuroplastic changes that promote retention and generalization of sensorimotor learning in patients. We highlight the benefits and limitations of letting therapists physically interact with patients through online control of robotic rehabilitation systems, and explore the concept of trust in human-robot interaction as it applies to patient-robot-therapist relationships. We conclude by highlighting several open questions to guide the future of therapist-in-the-loop rehabilitation robotics, including how much control to give therapists and possible approaches for having the robotic system learn from therapist-patient interactions.

  PublisherOA PDFDOI

Recent grants

• NIH Grant F32AR061238

  NIH · $79k · 2013

• NIH Grant F31EB005073

  NIH · $51k · 2009

Frequent coauthors

• Graham E. Caldwell

  University of Massachusetts Amherst

  21 shared

• Richard E.A. van Emmerik

  University of Massachusetts Amherst

  15 shared

• Paneed F. Jalili

  Universidad del Noreste

  10 shared

• Dagmar Sternad

  Northeastern University

  8 shared

• Sheng‐Che Yen

  8 shared

• Robert U. Newton

  University of Queensland

  6 shared

• Eric L. Dugan

  Texas Children's Hospital

  6 shared

• Julia Manczurowsky

  Northeastern University

  5 shared

Labs

• Department of Physical Therapy, Movement, and Rehabilitation SciencesPI

Education

• Ph.D., Physical Therapy

  University of ...

  2005

• M.S., Physical Therapy

  University of ...

  2002

• B.S., Physical Therapy

  University of ...

  1999