A pinboard by
Shriya Srinivasan

PhD Candidate, Harvard-MIT


Development of new surgical techniques for neural interfacing in the context of amputation.

I am working on creating a regenerative peripheral neural interfaces, which will enable amputees to directly control bionic prostheses and receive proprioceptive, or sensory, feedback in Dr. Hugh Herr's Biomechatronics Lab. This research combines novel surgical techniques with biomechatronics to push the boundaries of human-machine interfacing.


Long-term decoding of movement force and direction with a wireless myoelectric implant.

Abstract: The ease of use and number of degrees of freedom of current myoelectric hand prostheses is limited by the information content and reliability of the surface electromyography (sEMG) signals used to control them. For example, cross-talk limits the capacity to pick up signals from small or deep muscles, such as the forearm muscles for distal arm amputations, or sites of targeted muscle reinnervation (TMR) for proximal amputations. Here we test if signals recorded from the fully implanted, induction-powered wireless Myoplant system allow long-term decoding of continuous as well as discrete movement parameters with better reliability than equivalent sEMG recordings. The Myoplant system uses a centralized implant to transmit broadband EMG activity from four distributed bipolar epimysial electrodes.Two Rhesus macaques received implants in their backs, while electrodes were placed in their upper arm. One of the monkeys was trained to do a cursor task via a haptic robot, allowing us to control the forces exerted by the animal during arm movements. The second animal was trained to perform a center-out reaching task on a touchscreen. We compared the implanted system with concurrent sEMG recordings by evaluating our ability to decode time-varying force in one animal and discrete reach directions in the other from multiple features extracted from the raw EMG signals.In both cases, data from the implant allowed a decoder trained with data from a single day to maintain an accurate decoding performance during the following months, which was not the case for concurrent surface EMG recordings conducted simultaneously over the same muscles.These results show that a fully implantable, centralized wireless EMG system is particularly suited for long-term stable decoding of dynamic movements in demanding applications such as advanced forelimb prosthetics in a wide range of configurations (distal amputations, TMR).

Pub.: 09 Dec '15, Pinned: 25 Aug '17

Cutaneous sensory outcomes from three transhumeral targeted reinnervation cases.

Abstract: Although targeted muscle reinnervation has been shown to be effective in enhancing prosthetic control for upper limb amputees, restored hand sensations have been variable. An understanding of possible sensory feedback channels is crucial in working toward more effective closed-loop prosthetic control.To compare sensory outcomes of different targeted sensory reinnervation approaches.Case series, cross-sectional, and retrospective.Three transhumeral amputees that had undergone different sensory reinnervation approaches were recruited. Skin pressure sensitivity thresholds and anatomic sensory mapping were performed using Semmes-Weinstein monofilaments. The clinical charts of the subjects were reviewed to compare the sensory maps performed during the earlier post-reinnervation period.While the first two subjects achieved return of hand sensations on the stump skin in early follow-up, the maps showed attenuation over time. The last subject developed discrete sensations of all digits in the recipient cutaneous nerve territories away from the reinnervated muscles.These findings confirm that it is feasible to restore hand sensation after transhumeral targeted reinnervation, but there is a significant intersubject variability. The intrafascicular approach may be particularly effective in restoring digit sensation and deserves further exploration, as do factors affecting stability of the hand maps over time.In addition to enabling intuitive motor control of myoelectric prosthesis, targeted reinnervation can also result in sensory restoration of the hand. Documentation of sensory mapping present after reinnervation may assist with exploring future techniques for sensory enhancement, with the goal of working toward closed-loop prosthetic control.

Pub.: 05 Mar '16, Pinned: 25 Aug '17

In vivo characterization of regenerative peripheral nerve interface function.

Abstract: Regenerative peripheral nerve interfaces (RPNIs) are neurotized free autologous muscle grafts equipped with electrodes to record myoelectric signals for prosthesis control. Viability of rat RPNI constructs have been demonstrated using evoked responses. In vivo RPNI characterization is the next critical step for assessment as a control modality for prosthetic devices.Two RPNIs were created in each of two rats by grafting portions of free muscle to the ends of divided peripheral nerves (peroneal in the left and tibial in the right hind limb) and placing bipolar electrodes on the graft surface. After four months, we examined in vivo electromyographic signal activity and compared these signals to muscular electromyographic signals recorded from autologous muscles in two rats serving as controls. An additional group of two rats in which the autologous muscles were denervated served to quantify cross-talk in the electrode recordings. Recordings were made while rats walked on a treadmill and a motion capture system tracked the hind limbs. Amplitude and periodicity of signals relative to gait were quantified, correlation between electromyographic and motion recording were assessed, and a decoder was trained to predict joint motion.Raw RPNI signals were active during walking, with amplitudes of 1 mVPP, and quiet during standing, with amplitudes less than 0.1 mVPP. RPNI signals were periodic and entrained with gait. A decoder predicted bilateral ankle motion with greater than 80% reliability. Control group signal activity agreed with literature. Denervated group signals remained quiescent throughout all evaluations.In vivo myoelectric RPNI activity encodes neural activation patterns associated with gait. Signal contamination from muscles adjacent to the RPNI is minimal, as demonstrated by the low amplitude signals obtained from the Denervated group. The periodicity and entrainment to gait of RPNI recordings suggests the transduced signals were generated via central nervous system control.

Pub.: 10 Feb '16, Pinned: 25 Aug '17

Neural control of finger movement via intracortical brain-machine interface.

Abstract: Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques.In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex.Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ = 0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys' ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits/s throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter.This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step towards full and dexterous control of neural prosthetic devices.

Pub.: 20 Jul '17, Pinned: 25 Aug '17

A murine model of a novel surgical architecture for proprioceptive muscle feedback and its potential application to control of advanced limb prostheses.

Abstract: <i>Objective:</i> Proprioceptive mechanisms play a critical role in both reflexive and volitional lower extremity control. Significant strides have been made in the development of bionic limbs that are capable of bi-directional communication with the peripheral nervous system, but none of these systems have been capable of providing physiologically-relevant muscle-based proprioceptive feedback through natural neural pathways. In this study, we present the Agonist-antagonist Myoplastic Interface (AMI), a surgical approach with the capacity to provide graded kinesthetic feedback from a prosthesis through mechanical activation of native mechanoreceptors within residual agonist-antagonist muscle pairs. <i>Approach:</i> (1) Sonomicrometery and electroneurography measurement systems were validated using a servo-based muscle tensioning system. (2) A heuristic controller was implemented to modulate functional electrical stimulation (FES) of an agonist muscle, using sonomicrometric measurements of stretch from a mechanically-coupled antagonist muscle as feedback. (3) One AMI was surgically constructed in the hindlimb of each rat. (4) The gastrocnemius-soleus complex (GSC) of the rat was cycled through a series of ramp-and-hold stretches in two different muscle architectures: native (physiologically-intact) and AMI (modified). Integrated electroneurography (iENG) from the tibial nerve was compared across the two architectures. <i>Main results:</i> Correlation between stretch and afferent signal demonstrated that the AMI is capable of provoking graded afferent signals in response to ramp-and-hold stretches, in a manner similar to the native muscle architecture. The response magnitude in the AMI was reduced when compared to the native architecture, likely due to lower stretch amplitudes. The closed-loop control system showed robustness at high stretch magnitudes, with some oscillation at low stretch magnitudes. <i>Significance:</i> These results indicate that the AMI has the potential to communicate meaningful kinesthetic feedback from a prosthetic limb by replicating the agonist-antagonist relationships that are fundamental to physiological proprioception.

Pub.: 18 Feb '17, Pinned: 25 Aug '17