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      Restoration of natural thermal sensation in upper-limb amputees

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          Abstract

          The use of hands for gathering rich sensory information is essential for proper interaction with the environment; therefore, the restoration of sensation is critical for reestablishing the sense of embodiment in hand amputees. Here, we show that a noninvasive wearable device can be used to provide thermal sensations on amputees’ phantom hands. The device delivers thermal stimuli to specific regions of skin on their residual limb. These sensations were phenomenologically similar to those on the intact limbs and were stable over time. Using the device, the subjects could successfully exploit the thermal phantom hand maps to detect and discriminate different thermal stimuli. The use of a wearable device that provides thermal sensation can increase the sense of embodiment and improve life quality in hand amputees.

          Editor’s summary

          Recent advances in prosthesis development for upper-limb amputees have shown that it is possible to restore touch sensation using different approaches. However, current technologies do not allow the restoration of thermal sensation. To provide upper-limb amputees with a more natural feeling, Iberite et al . developed a noninvasive wearable device able to restore thermal sensation by delivering thermal stimuli in sensitive areas of the residual limb. Using this approach, they were able to elicit thermal phantom sensations. The amputees were able to discern different thermal stimuli reliably and consistently. The restoration of thermal sensation, in combination with existing technologies, will contribute to providing a close-to-natural experience in prosthesis users. —Mattia Maroso

          Abstract

          A wearable device can provide stable thermal sensation that is phenomenologically like natural sensations in hand amputees.

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          Most cited references17

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          Coding and use of tactile signals from the fingertips in object manipulation tasks.

          During object manipulation tasks, the brain selects and implements action-phase controllers that use sensory predictions and afferent signals to tailor motor output to the physical properties of the objects involved. Analysis of signals in tactile afferent neurons and central processes in humans reveals how contact events are encoded and used to monitor and update task performance.
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            The menthol receptor TRPM8 is the principal detector of environmental cold.

            Sensory nerve fibres can detect changes in temperature over a remarkably wide range, a process that has been proposed to involve direct activation of thermosensitive excitatory transient receptor potential (TRP) ion channels. One such channel--TRP melastatin 8 (TRPM8) or cold and menthol receptor 1 (CMR1)--is activated by chemical cooling agents (such as menthol) or when ambient temperatures drop below approximately 26 degrees C, suggesting that it mediates the detection of cold thermal stimuli by primary afferent sensory neurons. However, some studies have questioned the contribution of TRPM8 to cold detection or proposed that other excitatory or inhibitory channels are more critical to this sensory modality in vivo. Here we show that cultured sensory neurons and intact sensory nerve fibres from TRPM8-deficient mice exhibit profoundly diminished responses to cold. These animals also show clear behavioural deficits in their ability to discriminate between cold and warm surfaces, or to respond to evaporative cooling. At the same time, TRPM8 mutant mice are not completely insensitive to cold as they avoid contact with surfaces below 10 degrees C, albeit with reduced efficiency. Thus, our findings demonstrate an essential and predominant role for TRPM8 in thermosensation over a wide range of cold temperatures, validating the hypothesis that TRP channels are the principal sensors of thermal stimuli in the peripheral nervous system.
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              Restoring natural sensory feedback in real-time bidirectional hand prostheses.

              Hand loss is a highly disabling event that markedly affects the quality of life. To achieve a close to natural replacement for the lost hand, the user should be provided with the rich sensations that we naturally perceive when grasping or manipulating an object. Ideal bidirectional hand prostheses should involve both a reliable decoding of the user's intentions and the delivery of nearly "natural" sensory feedback through remnant afferent pathways, simultaneously and in real time. However, current hand prostheses fail to achieve these requirements, particularly because they lack any sensory feedback. We show that by stimulating the median and ulnar nerve fascicles using transversal multichannel intrafascicular electrodes, according to the information provided by the artificial sensors from a hand prosthesis, physiologically appropriate (near-natural) sensory information can be provided to an amputee during the real-time decoding of different grasping tasks to control a dexterous hand prosthesis. This feedback enabled the participant to effectively modulate the grasping force of the prosthesis with no visual or auditory feedback. Three different force levels were distinguished and consistently used by the subject. The results also demonstrate that a high complexity of perception can be obtained, allowing the subject to identify the stiffness and shape of three different objects by exploiting different characteristics of the elicited sensations. This approach could improve the efficacy and "life-like" quality of hand prostheses, resulting in a keystone strategy for the near-natural replacement of missing hands.
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                Author and article information

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                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                May 19 2023
                May 19 2023
                : 380
                : 6646
                : 731-735
                Affiliations
                [1 ]The BioRobotics Institute, Health Interdisciplinary Center, and Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy.
                [2 ]Bertarelli Foundation Chair in Translational Neural Engineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
                [3 ]Bertarelli Foundation Chair in Neuroprosthetic Technology, Neuro-X Institute, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
                [4 ]Bertarelli Foundation Chair in Cognitive Neuroprosthetics, Neuro-X Institute, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
                [5 ]Metaphysiks Engineering SA, 1260 Nyon, Switzerland.
                [6 ]Centro Protesi INAIL, 40054 Vigorso di Budrio, Italy.
                Article
                10.1126/science.adf6121
                37200444
                65662e47-819b-4dbd-8d8b-a6fedc20d595
                © 2023

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