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People use their hands for intricate tasks like playing musical instruments, employing myriad touch sensations to inform motor control. In contrast, current prosthetic hands lack comprehensive haptic feedback and exhibit rudimentary multitasking functionality. Limited research has explored the potential of upper limb amputees to feel, perceive, and respond to multiple channels of simultaneously activated haptic feedback to concurrently control the individual fingers of dexterous prosthetic hands. This study introduces a novel control architecture for three amputees and nine additional subjects to concurrently control individual fingers of an artificial hand using two channels of context-specific haptic feedback. Artificial neural networks (ANNs) recognize subjects’ electromyogram (EMG) patterns governing the artificial hand controller. ANNs also classify the directions objects slip across tactile sensors on the robotic fingertips, which are encoded via the vibration frequency of wearable vibrotactile actuators. Subjects implement control strategies with each finger simultaneously to prevent or permit slip as desired, achieving a 94.49% ± 8.79% overall success rate. Although no statistically significant difference exists between amputees’ and non-amputees’ success rates, amputees require more time to respond to simultaneous haptic feedback signals, suggesting a higher cognitive load. Nevertheless, amputees can accurately interpret multiple channels of nuanced haptic feedback to concurrently control individual robotic fingers, addressing the challenge of multitasking with dexterous prosthetic hands.
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This content will become publicly available on July 8, 2026
NURing: A Tendon-Driven Wearable Ring for On-Demand Kinesthetic Haptic Feedback
Not AvailableGenerating salient and intuitively understood haptic feedback on the human finger through a non-intrusive wearable remains a challenge in haptic device development. Most existing solutions either restrict the hand and finger’s natural range of motion or impede sensory perception, quickly becoming intrusive during dexterous manipulation tasks. Here, we introduce NURing (Non-intrUsive Ring), a tendon-actuated haptic device that provides kinesthetic feedback by deflecting the finger. The NURing is easily donned and doffed, enabling on-demand kinesthetic feedback while leaving the hand and fingers free for dexterous tasks. We demonstrate that the device delivers perceptually salient feedback and evaluate its performance through a series of uniaxial motion guidance tasks. The lightweight NURing device, measuring approximately 220 g, can generate guidance cues at up to 1 Hz, enabling participants to identify target directions in under 3 s with a 1.5° steady-state error, corresponding to a fingertip deviation of less than 11mm. Additionally, it can guide users along complex, smooth trajectories with an average trajectory error of 7°. These findings highlight the effectiveness of fingertip deflection as a kinesthetic feedback modality, enabling precise guidance for real-world applications such as sightless touchscreen navigation, assistive technology, and both industrial and consumer augmented/virtual reality systems.
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- Award ID(s):
- 2106191
- PAR ID:
- 10652000
- Publisher / Repository:
- IEEE
- Date Published:
- Page Range / eLocation ID:
- 255 to 266
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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