The InMotion ARM is an evidence based, intelligent interactive rehabilitation technology that senses patient movements and limitations, providing assistance-as-needed™ in real-time. It allows clinicians to efficiently deliver optimum intensive sensorimotor therapy to the shoulder and elbow to achieve the development of new neural pathways. The InMotion ARM has been sold in over 20 countries, including the United States for rehabilitation. Extensive research has shown it to be effective, especially for stroke and cerebral palsy
Clinical Degrees of Freedom
Task Specific Movement Training
Sample plots for a stroke patient at admission and discharge following robotic therapy
Circle Evaluation Test
(measures range of motor coordination, joint independence and coordinated movement planning).
Point to Point Evaluation Test
(measures control of changes in acceleration, speed, accuracy, and movement coordination).
The most thoroughly researched device for upper extremity neurorehabilitation
- 1000+ patients
- Large multi-site randomized controlled clinical trials
- Easy to use technology allows for high repetition
- 400-1000 reps/session
- Task specific to reduce impairments in the affected limb(s) focusing on improving patient’s:
- Range of Motion
- Movement Speed
- Movement Smoothness
- Easy-to-use, grab and go set up
- Direct wheel chair access
- Print patient progress reports directly from the robot
Broad clinical application shown to improve functional outcomes across the continuum of care.1
InMotion ARMTM Software
Intensive — 1024 movements per therapy session with evidence-based treatment protocols.
Therapy protocols allowing clinicians to customize treatment. Therapeutic exercise games for:
- Motor planning
- Eye-hand coordination
- Attention, visual field deficits/neglect
- Massed practice
2D Gravity Compensated Therapy is more effective than 3D Spatial Therapy
IMT’s modular, “gym-of-robots” systems approach to neurorehabilitation is the only system designed to optimize the use of robotics for neurorehabilitation in a manner that is consistent with the latest clinical research and neuroscience, taking into account the latest understandings on motor learning interference and motor memory consolidation. For instance, training planar and vertical (anti-gravity) movements in alternate days leads to better outcomes than training during the same session2.
By measuring patient kinematic and kinetic data objectively, IMT’s robots have shown that for severe to moderate brain injury the effectiveness of therapy is optimized by allowing the robots to focus on reducing impairment and allowing the therapist to assist on translating the gains in impairment into function.
InMotion ARM™ Dimensions
Workstation: 44”(1.12m)(W) x 73” (1.85m)(D) x 45” (1.2m)(H) at lowest position. Allow 32″(.81m) for chair.
185 lbs. (83kg)
100 – 240VAC, 50/60Hz, automatic <1250VA.
Quantifies upper extremity motor control and movement recovery allowing clinicians to distinguish true recovery from compensation
Establishes a baseline and measures progress to:
- Determine medical necessity
- Justify continuation of treatment based upon measurable gains
Quantifiable measures for:
- Shoulder stabilization
- Smoothness of Arm movement
- Arms ability to move against resistance
- Mean and Maximum arm speed
- Arm Reaching error
- Joint independence
Correlated with traditional assessment scales:
Fugl-meyer, Motor-Power and NIH stroke scale performance*
Maximum Shoulder Force
Optional InMotion Eval module.
Allows clinicians to measure a patient’s ability to generate maximum shoulder flexion/extension, adduction/abduction force.
Custom Designed Technology
6 degree-of-freedom force-torque sensor monolithic aluminum device containing analog and digital electronics systems.
Module attaches to the InMotion ARM™ Robot.
* Bosecker Caittlyn MS, Dipietro Laura, Volpe BT, Krebs HI “Kinematic Robot-Based Evaluation Scales and Clinical Counterparts to Measure Upper Limb Motor Performance in Patients With Chronic Stroke” Neurorehabilitation and Neural Repair 24(1) 62-69 , 2010.
1 Robot training enhanced motor outcome in patients with stroke maintained over 3 years. Neurology. Volpe BT, Krebs HI, Hogan N, Edelsteinn L, Diels CM, Aisen ML. 1999;53:1874 –1876.
2 Krebs, H.I., et al., “Rehabilitation Robotics: Pilot Trial of a Spatial Extension for MIT-MANUS,” Journal of NeruoEngineering and Rehabilitation, Biomedcentral, 1:5 (2004)
Klein Julius, Spencer Steven J,Reinkensmeyer David J. “Breaking It Down Is Better: Haptic Decomposition of Complex Movements Aids in Robot-Assisted Motor Learning” ieee Transactions On Neural Systems And Rehabilitation Engineering, VOL. 20, NO. 3, MAY 2012
Krakauer John W, Carmichael Thomas S, Corbett Dale, Wittenberg George F, “Getting neurorehabilitation right: What Can Be Learned From Animal Models?” Neurorehabilitation and Neural Repair, published online March 30 2012
Dipietro, H.I. Krebs, B.T. Volpe, J. Stein, C. Bever, S.T. Mernoff, S.E. Fasoli, and N. Hogan “Learning, not Adaptation, Characterizes Stroke Motor Recovery: Evidence from Kinematic Changes Induced by Robot-Assisted Therapy in Trained and Untrained Task in the Same Workspace.” IEEE transactions on neural systems and rehabilitation engineering 2012 Jan:20(1):48-57