Mathew Kollamkulam

University College London

Papers

2

Total Citations

21

H-Index

2

About

Mathew Kollamkulam investigates the intersection of somatosensory feedback and motor learning, with a focus on augmentative and prosthetic technologies. His work explores how intrinsic somatosensory signals from the body parts controlling artificial limbs—such as extra robotic fingers—can support motor control and skill acquisition without relying on artificial sensory substitution. In his most cited paper, "Intrinsic somatosensory feedback supports motor control and learning to operate artificial body parts" (2022, 19 citations), Kollamkulam demonstrates that natural proprioceptive and tactile cues from the controller’s own body enhance performance and learning in operating artificial appendages. A related study (2021, 2 citations) extends these findings to augmentative devices, showing that somatosensory information from the controlling body part facilitates motor learning. His research challenges the prevailing emphasis on artificial feedback, suggesting that intrinsic signals are often sufficient and more effective. Kollamkulam’s contributions are significant for designing intuitive, user-friendly neuroprosthetics and augmentative tools, with implications for rehabilitation and human augmentation. His work is gaining traction among researchers in motor neuroscience and bionics.

Research Focus

Key Achievements

2
H-Index
2
Papers
21
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Intrinsic somatosensory feedback supports motor control and learning to operate artificial body parts
19 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University College London

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago