Research ArticleNEUROPROSTHETICS

Enhancing functional abilities and cognitive integration of the lower limb prosthesis

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Science Translational Medicine  02 Oct 2019:
Vol. 11, Issue 512, eaav8939
DOI: 10.1126/scitranslmed.aav8939
  • Fig. 1 Neuroprosthetic leg.

    The lower limb amputees wear a custom-made prosthesis with commercially available knee and ankle components equipped with a system for restoring sensory feedback. An encoder is embedded in the prosthetic knee (A) indicating the amount of flexion of the device and a sensorized insole is placed under the prosthetic foot. The readout from these sensors is transmitted via Bluetooth as input to an external controller, which translates it into the language of the nerve, meaning the parameters of stimulation. These instructions drive the activity of an external stimulator, which is connected to four transversal intrafascicular multichannel electrodes (TIMEs), previously implanted into the tibial portion of the sciatic nerve (B). The neural interfaces are placed transversally in the nerve, inside the fascicles.

  • Fig. 2 Characterization of the evoked sensations.

    (A) The distribution of the sensation type for each subject according to all the phantom sensations evoked in the first month by every active site. (B) Distribution of sensations over the lower limb. The lower limb is divided into four areas representing the muscles innervated by the tibial nerve (A, gastrocnemius caput medialis; B, gastrocnemius caput lateralis; C, soleus; and D, posterior ankle). The bar plots show the percentage and number of active sites eliciting sensations on the lower limb for each subject. (C) The maps of foot sensations and the bar plots with the number of active sites eliciting sensations for each subject are reported. Each colored area indicates the 75th percentile of the phantom sensation evoked for an active site (the most frequently reported). The maps are related to the first month of each implant.

  • Fig. 3 Sensory feedback restoration system calibration and real-time use.

    (A) Step 1: A custom-made software was developed to control the stimuli injected through the stimulators into the TIME electrodes and to record the reports corresponding to the evoked sensations. The stimuli are balanced, symmetric cathodic first trains of rectangular pulses. Desired amplitude, pulsewidth, and frequency were inserted by the operator. The active sites, whose stimulation elicited a tactile percept in the locations matching the areas of placements of the sensorized insole, were selected. In addition, an active site evoking a muscle contraction of the calf was saved for further use in the sensory feedback restoration device. Along with these values, the minimum charge to elicit a sensation and the threshold to pain were saved. (B) Step 2: The parameters of stimulation identified are used to calibrate the encoding algorithm, running on the external controller. The encoder transduces the data from the sensorized insole and the knee encoder (Bluetooth communication) into execution instructions for the external stimulator. The function transfer between these two sets of values is linear. To calibrate it, the subgroup of channels to read from the sensorized insole and knee encoder, the minimum and maximum values of their readout, the minimum and maximum active sites charges, and the corresponding stimulator channels to activate are needed. (C) Step 3: the instructions of stimulation are delivered in real-time. The stimulator injects into the TIMEs balanced, symmetric cathodic first trains of rectangular pulses of fixed frequency and pulse width and amplitude variable with respect to the real-time sensors’ readouts.

  • Fig. 4 Passive recognition tasks.

    (A) The touch task and its performance. Up to four positions on the foot sole were chosen and randomly touched by the experimenter. A nontouch condition was also used. The plots show how the current was injected according to the position touched. For S3, the medial metatarsus position was replaced with the hallux one. n = 92 repetitions for S1, n = 120 for S2, n = 140 for S3. (B) The proprioception task and its performance. Four random angles of the knee were transmitted to the subjects. The plots show how the charge was modulated according to the angle. n = 72 repetitions for S1, n = 120 for S2; n = 120 for S3. (C) The combined task and its performance. Different combinations of touch and angle were induced to the subjects. The plots show how the current was injected and modulated according to the angle and the position under the sole touched. n = 72 repetitions for S1, n = 308 for S2, n = 180 for S3. In (A) to (C), the circles indicate the partial performance for every condition, whereas the dashed lines show the chance levels.

  • Fig. 5 Sensory feedback-improved walking performance of amputees.

    (A) Top: A subject while climbing (first picture) and descending stairs (last one). Middle (from top to bottom): prosthetic ankle trajectory of a subject while climbing and descending stairs for one lap (extracted from camera recordings in the parallel plane to motion), synchronous sensorized insole and knee encoder readouts, and encoded currents injected into the TIMEs. Bottom: The mean number ± SD of laps/session with proprioception + touch (PT), touch (T), proprioception (P) conditions, and without stimulation (NF) during stairs tests for S1, S2 and S3. n = 12 sessions per condition. (B) Top: A subject passing over an obstacle without falling (representation on the left) and falling (one on the right). Middle (from top to bottom): trajectories of ankle, knee, and hip of prosthetic and healthy sides of a subject while walking on the obstacle path (extracted from camera recordings in the orthogonal plane to motion). Four steps are shown: passing without falling on an obstacle (also in pictures), two steps with no obstacle, falling due to an obstacle (also in pictures); synchronous sensorized insole and knee encoder readouts, and encoded currents injected into the TIMEs. Bottom: The mean number ± SD of falls versus total trampled obstacles per session with PT, T, P, and NF during obstacles test for S1, S2, and S3. n = 12 sessions per condition. (C) Top. A subject while executing the straight-line test: a subject steps on the line, then off, and finally on it again. Middle (from top to bottom): distance between the prosthetic foot and the straight line of a subject (extracted from camera recordings as shown in the scheme on the right), during the execution of the three steps, synchronous sensorized insole and knee readouts, and encoded currents injected into the TIMEs. Bottom: The mean number ± SD of steps off the straight line of all the steps performed with PT and NF during straight line tests for S1, S2, and S3. n = 9 sessions per condition. *P < 0.05. Two-tailed ANOVA test with Tukey-Kramer correction for multiple groups of data was performed.

  • Fig. 6 Sensory feedback-improved embodiment and cognitive burden.

    The embodiment was assessed through proprioceptive displacement and questionnaires after the execution of the functional tasks. Four conditions were evaluated: NF, P or T, and PT. (A) On the left, a subject lies down on a bed during the measurement of the proprioceptive displacement executed with the aid of a shaft moving into a rail. The subject cannot see his feet. From the left to the right, after the picture, there are the: answers to embodiment questions 1 to 3 (control questions were always replied with −3), vividness and prevalence rating, and the proprioceptive displacement, respectively. S2 and S3 are in order on the top and on the bottom. For embodiment questionnaire n = 30, for vividness and prevalence n = 10, for phantom foot displacement n = 30. Two-tailed ANOVA test with Tukey-Kramer correction for multiple groups of data was performed. *P < 0.05. The cognitive effort made by the subjects during the walking activity was evaluated through acoustic event-related potentials (ERPs). (B) The subjects were asked to repeatedly count sounds that were delivered during three conditions: sitting, walking with (PT) and without neural stimulation. Because the same participant was repeating several sessions of the experiment, we varied the occurrence timings of all tones and the number of target and deviant tones: The number of standard tones was always the same (342), whereas the number of target and deviant tones varied between 41 and 46. The topographical representations of the voltage distribution in the P300 time window are depicted, confirming that the P300 component was present in the target trials because it is the most prominent over the parietocentral scalp locations. The ERPs are plotted in Pz location. Red and black represent walking with and without feedback, whereas blue is sitting. 3 × 2 ANOVA (control/walking with stimulation/walking without stimulation × target/non-target) was executed among averages computed in the P300 time window [450, 650] ms. The two-tailed Greenhouse-Geisser correction for multiple groups of data was applied. Averages are on n = 38 trials for both the target and deviant tones, which were not disregarded after data processing. *P < 0.01.

Supplementary Materials

  • stm.sciencemag.org/cgi/content/full/11/512/eaav8939/DC1

    Fig. S1. Perceived magnitude scale of the evoked sensations.

    Fig. S2. Stimulation parameters in the neuroprosthesis.

    Fig. S3. Passive task individual confusion matrices.

    Fig. S4. Control condition passive tasks.

    Fig. S5. Validation measures during obstacles.

    Fig. S6. Validation measures during straight line.

    Fig. S7. Validation measures of cognitive load assessing.

    Table S1. Active sites-sensations correspondence.

    Table S2. Embodiment questionnaire.

    Movie S1. Neuroprosthesis restores missing leg sensations.

    Movie S2. Neuroprosthesis working principle and active tasks.

    Data file S1. Raw data for distributions from all the figures in the main text and supplementary materials.

  • The PDF file includes:

    • Fig. S1. Perceived magnitude scale of the evoked sensations.
    • Fig. S2. Stimulation parameters in the neuroprosthesis.
    • Fig. S3. Passive task individual confusion matrices.
    • Fig. S4. Control condition passive tasks.
    • Fig. S5. Validation measures during obstacles.
    • Fig. S6. Validation measures during straight line.
    • Fig. S7. Validation measures of cognitive load assessing.
    • Table S1. Active sites-sensations correspondence.
    • Table S2. Embodiment questionnaire.
    • Legends for movies S1 and S2
    • Legend for data file S1

    [Download PDF]

    Other Supplementary Material for this manuscript includes the following:

    • Movie S1 (.mov format). Neuroprosthesis restores missing leg sensations.
    • Movie S2 (.mov format). Neuroprosthesis working principle and active tasks.
    • Data file S1 (Microsoft Excel format). Raw data for distributions from all the figures in the main text and supplementary materials.

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