Maria Bengtson
Papers
5
Total Citations
74
H-Index
4
About
Maria Bengtson’s research sits at the intersection of robotics, neuroscience, and stroke rehabilitation, with a focus on restoring sensorimotor function in the upper limb. Her major contributions center on developing novel, objective methods to assess and treat proprioceptive deficits—the loss of body position awareness—following stroke. She created the Arm Movement Detection (AMD) test, a fast robotic assessment that yields a ratio-scaled measure of proprioceptive acuity, providing clinicians with a reliable tool to evaluate sensory impairments and their impact on motor control. This work, cited over 29 times, has been validated for its reliability and clinical utility. Bengtson also explored the potential of tactile proprioceptive input as artificial feedback to compensate for lost sensation, a promising avenue for robotic rehabilitation after stroke. More recently, she has advanced the spatial mapping of posture-dependent resistance in hypertonic arms, offering a systematic way to quantify abnormal neuromuscular mechanics across the reachable workspace. Her cumulative citation impact, exceeding 70 citations, underscores the relevance of her work to both rehabilitation engineering and clinical neuroscience.
Research Focus
Key Achievements
Top Papers
- 1
- 2Tactile proprioceptive input in robotic rehabilitation after stroke27 citations · 2015
- 3
- 4The arm motion detection (AMD) test5 citations · 2014
- 5