Building biosecurity for synthetic biology.

The fast-paced field of synthetic biology is fundamentally changing the global biosecurity framework. Current biosecurity regulations and strategies are based on previous governance paradigms for pathogen-oriented security, recombinant DNA research, and broader concerns related to genetically modified organisms (GMOs). Many scholarly discussions and biosecurity practitioners are therefore concerned that synthetic biology outpaces established biosafety and biosecurity measures to prevent deliberate and malicious or inadvertent and accidental misuse of synthetic biology's processes or products. This commentary proposes three strategies to improve biosecurity: Security must be treated as an investment in the future applicability of the technology; social scientists and policy makers should be engaged early in technology development and forecasting; and coordination among global stakeholders is necessary to ensure acceptable levels of risk.

Targeted Muscle Reinnervation Treats Neuroma and Phantom Pain in Major Limb Amputees: A Randomized Clinical Trial.

OBJECTIVE: To compare targeted muscle reinnervation (TMR) to "standard treatment" of neuroma excision and burying into muscle for postamputation pain. SUMMARY BACKGROUND DATA: To date, no intervention is consistently effective for neuroma-related residual limb or phantom limb pain (PLP). TMR is a nerve transfer procedure developed for prosthesis control, incidentally found to improve postamputation pain. METHODS: A prospective, randomized clinical trial was conducted. 28 amputees with chronic pain were assigned to standard treatment or TMR. Primary outcome was change between pre- and postoperative numerical rating scale (NRS, 0-10) pain scores for residual limb pain and PLP at 1 year. Secondary outcomes included NRS for all patients at final follow-up, PROMIS pain scales, neuroma size, and patient function. RESULTS: In intention-to-treat analysis, changes in PLP scores at 1 year were 3.2 versus -0.2 (difference 3.4, adjusted confidence interval (aCI) -0.1 to 6.9, adjusted P = 0.06) for TMR and standard treatment, respectively. Changes in residual limb pain scores were 2.9 versus 0.9 (difference 1.9, aCI -0.5 to 4.4, P = 0.15). In longitudinal mixed model analysis, difference in change scores for PLP was significantly greater in the TMR group compared with standard treatment [mean (aCI) = 3.5 (0.6, 6.3), P = 0.03]. Reduction in residual limb pain was favorable for TMR (P = 0.10). At longest follow-up, including 3 crossover patients, results favored TMR over standard treatment. CONCLUSIONS: In this first surgical RCT for the treatment of postamputation pain in major limb amputees, TMR improved PLP and trended toward improved residual limb pain compared with conventional neurectomy. TRIAL REGISTRATION: NCT02205385 at ClinicalTrials.gov.

Articulating 'free, prior and informed consent' (FPIC) for engineered gene drives.

Recent statements by United Nations bodies point to free, prior and informed consent (FPIC) as a potential requirement in the development of engineered gene drive applications. As a concept developed in the context of protecting Indigenous rights to self-determination in land development scenarios, FPIC would need to be extended to apply to the context of ecological editing. Without an explicit framework of application, FPIC could be interpreted as a narrowly framed process of community consultation focused on the social implications of technology, and award little formal or advisory power in decision-making to Indigenous peoples and local communities. In this paper, we argue for an articulation of FPIC that attends to issues of transparency, iterative community-scale consent, and shared power through co-development among Indigenous peoples, local communities, researchers and technology developers. In realizing a comprehensive FPIC process, researchers and developers have an opportunity to incorporate enhanced participation and social guidance mechanisms into the design, development and implementation of engineered gene drive applications.

Upper limb cortical maps in amputees with targeted muscle and sensory reinnervation.

Neuroprosthetics research in amputee patients aims at developing new prostheses that move and feel like real limbs. Targeted muscle and sensory reinnervation (TMSR) is such an approach and consists of rerouting motor and sensory nerves from the residual limb towards intact muscles and skin regions. Movement of the myoelectric prosthesis is enabled via decoded electromyography activity from reinnervated muscles and touch sensation on the missing limb is enabled by stimulation of the reinnervated skin areas. Here we ask whether and how motor control and redirected somatosensory stimulation provided via TMSR affected the maps of the upper limb in primary motor (M1) and primary somatosensory (S1) cortex, as well as their functional connections. To this aim, we tested three TMSR patients and investigated the extent, strength, and topographical organization of the missing limb and several control body regions in M1 and S1 at ultra high-field (7 T) functional magnetic resonance imaging. Additionally, we analysed the functional connectivity between M1 and S1 and of both these regions with fronto-parietal regions, known to be important for multisensory upper limb processing. These data were compared with those of control amputee patients (n = 6) and healthy controls (n = 12). We found that M1 maps of the amputated limb in TMSR patients were similar in terms of extent, strength, and topography to healthy controls and different from non-TMSR patients. S1 maps of TMSR patients were also more similar to normal conditions in terms of topographical organization and extent, as compared to non-targeted muscle and sensory reinnervation patients, but weaker in activation strength compared to healthy controls. Functional connectivity in TMSR patients between upper limb maps in M1 and S1 was comparable with healthy controls, while being reduced in non-TMSR patients. However, connectivity was reduced between S1 and fronto-parietal regions, in both the TMSR and non-TMSR patients with respect to healthy controls. This was associated with the absence of a well-established multisensory effect (visual enhancement of touch) in TMSR patients. Collectively, these results show how M1 and S1 process signals related to movement and touch are enabled by targeted muscle and sensory reinnervation. Moreover, they suggest that TMSR may counteract maladaptive cortical plasticity typically found after limb loss, in M1, partially in S1, and in their mutual connectivity. The lack of multisensory interaction in the present data suggests that further engineering advances are necessary (e.g. the integration of somatosensory feedback into current prostheses) to enable prostheses that move and feel as real limbs.

Control within a virtual environment is correlated to functional outcomes when using a physical prosthesis.

BACKGROUND: Advances such as targeted muscle reinnervation and pattern recognition control may provide improved control of upper limb myoelectric prostheses, but evaluating user function remains challenging. Virtual environments are cost-effective and immersive tools that are increasingly used to provide practice and evaluate prosthesis control, but the relationship between virtual and physical outcomes-i.e., whether practice in a virtual environment translates to improved physical performance-is not understood. METHODS: Nine people with transhumeral amputations who previously had targeted muscle reinnervation surgery were fitted with a myoelectric prosthesis comprising a commercially available elbow, wrist, terminal device, and pattern recognition control system. Virtual and physical outcome measures were obtained before and after a 6-week home trial of the prosthesis. RESULTS: After the home trial, subjects showed statistically significant improvements (p < 0.05) in offline classification error, the virtual Target Achievement Control test, and the physical Southampton Hand Assessment Procedure and Box and Blocks Test. A trend toward improvement was also observed in the physical Clothespin Relocation task and Jebsen-Taylor test; however, these changes were not statistically significant. The median completion time in the virtual test correlated strongly and significantly with the Southampton Hand Assessment Procedure (p = 0.05, R = - 0.86), Box and Blocks Test (p = 0.007, R = - 0.82), Jebsen-Taylor Test (p = 0.003, R = 0.87), and the Assessment of Capacity for Myoelectric Control (p = 0.005,R = - 0.85). The classification error performance only had a significant correlation with the Clothespin Relocation Test (p = 0.018, R = .76). CONCLUSIONS: In-home practice with a pattern recognition-controlled prosthesis improves functional control, as measured by both virtual and physical outcome measures. However, virtual measures need to be validated and standardized to ensure reliability in a clinical or research setting. TRIAL REGISTRATION: This is a registered clinical trial: NCT03097978 .

Resolving the effect of wrist position on myoelectric pattern recognition control.

BACKGROUND: The use of pattern recognition-based methods to control myoelectric upper-limb prostheses has been well studied in individuals with high-level amputations but few studies have demonstrated that it is suitable for partial-hand amputees, who often possess a functional wrist. This study's objective was to evaluate strategies that allow partial-hand amputees to control a prosthetic hand while allowing retain wrist function. METHODS: EMG data was recorded from the extrinsic and intrinsic hand muscles of six non-amputees and two partial-hand amputees while they performed 4 hand motions in 13 different wrist positions. The performance of 4 classification schemes using EMG data alone and EMG data combined with wrist positional information was evaluated. Using recorded wrist positional data, the relationship between EMG features and wrist position was modeled and used to develop a wrist position-independent classification scheme. RESULTS: A multi-layer perceptron artificial neural network classifier was better able to discriminate four hand motion classes in 13 wrist positions than a linear discriminant analysis classifier (p = 0.006), quadratic discriminant analysis classifier (p < 0.0001) and a linear perceptron artificial neural network classifier (p = 0.04). The addition of wrist position data to EMG data significantly improved performance (p < 0.001). Training the classifier with the combination of extrinsic and intrinsic muscle EMG data performed significantly better than using intrinsic (p < 0.0001) or extrinsic muscle EMG data alone (p < 0.0001), and training with intrinsic muscle EMG data performed significantly better than extrinsic muscle EMG data alone (p < 0.001). The same trends were observed for amputees, except training with intrinsic muscle EMG data, on average, performed worse than the extrinsic muscle EMG data. We propose a wrist position-independent controller that simulates data from multiple wrist positions and is able to significantly improve performance by 48-74% (p < 0.05) for non-amputees and by 45-66% for partial-hand amputees, compared to a classifier trained only with data from a neutral wrist position and tested with data from multiple positions. CONCLUSIONS: Sensor fusion (using EMG and wrist position information), non-linear artificial neural networks, combining EMG data across multiple muscle sources, and simulating data from different wrist positions are effective strategies for mitigating the wrist position effect and improving classification performance.

How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR's Rehabilitation Engineering Research Centers.

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a "total approach to rehabilitation", combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970's, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program.

Targeted Muscle Reinnervation for the Upper and Lower Extremity.

Myoelectric devices are controlled by electromyographic signals generated by contraction of residual muscles, which thus serve as biological amplifiers of neural control signals. Although nerves severed by amputation continue to carry motor control information intended for the missing limb, loss of muscle effectors due to amputation prevents access to this important control information. Targeted Muscle Reinnervation (TMR) was developed as a novel strategy to improve control of myoelectric upper limb prostheses. Severed motor nerves are surgically transferred to the motor points of denervated target muscles, which, after reinnervation, contract in response to neural control signals for the missing limb. TMR creates additional control sites, eliminating the need to switch the prosthesis between different control modes. In addition, contraction of target muscles, and operation of the prosthesis, occurs in reponse to attempts to move the missing limb, making control easier and more intuitive. TMR has been performed extensively in individuals with high-level upper limb amputations and has been shown to improve functional prosthesis control. The benefits of TMR are being studied in individuals with transradial amputations and lower limb amputations. TMR is also being investigated in an ongoing clinical trial as a method to prevent or treat painful amputation neuromas.

Robotic leg control with EMG decoding in an amputee with nerve transfers.

The clinical application of robotic technology to powered prosthetic knees and ankles is limited by the lack of a robust control strategy. We found that the use of electromyographic (EMG) signals from natively innervated and surgically reinnervated residual thigh muscles in a patient who had undergone knee amputation improved control of a robotic leg prosthesis. EMG signals were decoded with a pattern-recognition algorithm and combined with data from sensors on the prosthesis to interpret the patient's intended movements. This provided robust and intuitive control of ambulation--with seamless transitions between walking on level ground, stairs, and ramps--and of the ability to reposition the leg while the patient was seated.

Transfemoral amputee recovery strategies following trips to their sound and prosthesis sides throughout swing phase.

BACKGROUND: Recovering from trips is challenging for transfemoral amputees, and attempts often result in falls. Better understanding of the effects of the sensory-motor deficits brought by amputation and the functional limitations of prosthetic devices could help guide therapy and fall prevention mechanisms in prostheses. However, how transfemoral amputees attempt to recover from trips on the sound and prosthesis sides throughout swing phase is poorly understood. METHODS: We tripped eight able-bodied subjects and eight unilateral transfemoral amputees wearing their prescribed prostheses. The protocol consisted of six repetitions of 6 and 4 points throughout swing phase, respectively. We compared recovery strategies in able-bodied, sound side and prosthesis side limbs. The number of kinematic recovery strategies used, when they were used throughout swing phase, and kinematic characteristics (tripped limb joint angles, bilateral trochanter height and time from foot arrest to foot strike) of each strategy were compared across limb groups. Non-parametric statistical tests with corrections for post-hoc tests were used. RESULTS: Amputees used the same recovery strategies as able-bodied subjects on both sound and prosthesis sides, although not all subjects used all strategies. Compared to able-bodied subjects, amputees used delayed-lowering strategies less often from 30-60 % of swing phase on the sound side, and from 45-60 % of swing phase on the prosthesis side. Within-strategy kinematic differences occurred across limbs; however, these differences were not consistent across all strategies. Amputee-specific recovery strategies-that are not used by control subjects-occurred following trips on both the sound and prosthesis sides in mid- to late swing. CONCLUSIONS: Collectively, these results suggest that sensory input from the distal tripped leg is not necessary to trigger able-bodied trip recovery strategies. In addition, the differences between sound and prosthesis side recoveries indicate that the ability of the support leg might be more critical than that of the tripped leg when determining the response to a trip. The outcomes of this study have implications for prosthesis control, suggesting that providing correct and intuitive real-time selection of typical able-bodied recovery strategies by a prosthetic device when it is the tripped and the support limb could better enable balance recovery and avoid falls.

Intuitive control of a powered prosthetic leg during ambulation: a randomized clinical trial.

IMPORTANCE: Some patients with lower leg amputations may be candidates for motorized prosthetic limbs. Optimal control of such devices requires accurate classification of the patient's ambulation mode (eg, on level ground or ascending stairs) and natural transitions between different ambulation modes. OBJECTIVE: To determine the effect of including electromyographic (EMG) data and historical information from prior gait strides in a real-time control system for a powered prosthetic leg capable of level-ground walking, stair ascent and descent, ramp ascent and descent, and natural transitions between these ambulation modes. DESIGN, SETTING, AND PARTICIPANTS: Blinded, randomized crossover clinical trial conducted between August 2012 and November 2013 in a research laboratory at the Rehabilitation Institute of Chicago. Participants were 7 patients with unilateral above-knee (n = 6) or knee-disarticulation (n = 1) amputations. All patients were capable of ambulation within their home and community using a passive prosthesis (ie, one that does not provide external power). INTERVENTIONS: Electrodes were placed over 9 residual limb muscles and EMG signals were recorded as patients ambulated and completed 20 circuit trials involving level-ground walking, ramp ascent and descent, and stair ascent and descent. Data were acquired simultaneously from 13 mechanical sensors embedded on the prosthesis. Two real-time pattern recognition algorithms, using either (1) mechanical sensor data alone or (2) mechanical sensor data in combination with EMG data and historical information from earlier in the gait cycle, were evaluated. The order in which patients used each configuration was randomized (1:1 blocked randomization) and double-blinded so patients and experimenters did not know which control configuration was being used. MAIN OUTCOMES AND MEASURES: The main outcome of the study was classification error for each real-time control system. Classification error is defined as the percentage of steps incorrectly predicted by the control system. RESULTS: Including EMG signals and historical information in the real-time control system resulted in significantly lower classification error (mean, 7.9% [95% CI, 6.1%-9.7%]) across a mean of 683 steps (range, 640-756 steps) compared with using mechanical sensor data only (mean, 14.1% [95% CI, 9.3%-18.9%]) across a mean of 692 steps (range, 631-775 steps), with a mean difference between groups of 6.2% (95% CI, 2.7%-9.7%] (P = .01). CONCLUSIONS AND RELEVANCE: In this study of 7 patients with lower limb amputations, inclusion of EMG signals and temporal gait information reduced classification error across ambulation modes and during transitions between ambulation modes. These preliminary findings, if confirmed, have the potential to improve the control of powered leg prostheses.

Targeted muscle reinnervation: a novel approach to postamputation neuroma pain.

BACKGROUND: Postamputation neuroma pain can prevent comfortable prosthesis wear in patients with limb amputations, and currently available treatments are not consistently effective. Targeted muscle reinnervation (TMR) is a decade-old technique that employs a series of novel nerve transfers to permit intuitive control of upper-limb prostheses. Clinical experience suggests that it may also serve as an effective therapy for postamputation neuroma pain; however, this has not been explicitly studied. QUESTIONS/PURPOSES: We evaluated the effect of TMR on residual limb neuroma pain in upper-extremity amputees. METHODS: We conducted a retrospective medical record review of all 28 patients treated with TMR from 2002 to 2012 at Northwestern Memorial Hospital/Rehabilitation Institute of Chicago (Chicago, IL, USA) and San Antonio Military Medical Center (San Antonio, TX, USA). Twenty-six of 28 patients had sufficient (> 6 months) followup for study inclusion. The amputation levels were shoulder disarticulation (10 patients) and transhumeral (16 patients). All patients underwent TMR for the primary purpose of improved myoelectric control. Of the 26 patients included in the study, 15 patients had evidence of postamputation neuroma pain before undergoing TMR. RESULTS: Of the 15 patients presenting with neuroma pain before TMR, 14 experienced complete resolution of pain in the transferred nerves, and the remaining patient's pain improved (though did not resolve). None of the patients who presented without evidence of postamputation neuroma pain developed neuroma pain after the TMR procedure. All 26 patients were fitted with a prosthesis, and 23 of the 26 patients were able to operate a TMR-controlled prosthesis. CONCLUSIONS: None of the 26 patients who underwent TMR demonstrated evidence of new neuroma pain after the procedure, and all but one of the 15 patients who presented with preoperative neuroma pain experienced complete relief of pain in the distribution of the transferred nerves. TMR offers a novel and potentially more effective therapy for the management of neuroma pain after limb amputation.

Activation of individual extrinsic thumb muscles and compartments of extrinsic finger muscles.

Mechanical and neurological couplings exist between musculotendon units of the human hand and digits. Studies have begun to understand how these muscles interact when accomplishing everyday tasks, but there are still unanswered questions regarding the control limitations of individual muscles. Using intramuscular electromyographic (EMG) electrodes, this study examined subjects' ability to individually initiate and sustain three levels of normalized muscular activity in the index and middle finger muscle compartments of extensor digitorum communis (EDC), flexor digitorum profundus (FDP), and flexor digitorum superficialis (FDS), as well as the extrinsic thumb muscles abductor pollicis longus (APL), extensor pollicis brevis (EPB), extensor pollicis longus (EPL), and flexor pollicis longus (FPL). The index and middle finger compartments each sustained activations with significantly different levels of coactivity from the other finger muscle compartments. The middle finger compartment of EDC was the exception. Only two extrinsic thumb muscles, EPL and FPL, were capable of sustaining individual activations from the other thumb muscles, at all tested activity levels. Activation of APL was achieved at 20 and 30% MVC activity levels with significantly different levels of coactivity. Activation of EPB elicited coactivity levels from EPL and APL that were not significantly different. These results suggest that most finger muscle compartments receive unique motor commands, but of the four thumb muscles, only EPL and FPL were capable of individually activating. This work is encouraging for the neural control of prosthetic limbs because these muscles and compartments may potentially serve as additional user inputs to command prostheses.

Development of a mechatronic platform and validation of methods for estimating ankle stiffness during the stance phase of walking.

The mechanical properties of human joints (i.e., impedance) are constantly modulated to precisely govern human interaction with the environment. The estimation of these properties requires the displacement of the joint from its intended motion and a subsequent analysis to determine the relationship between the imposed perturbation and the resultant joint torque. There has been much investigation into the estimation of upper-extremity joint impedance during dynamic activities, yet the estimation of ankle impedance during walking has remained a challenge. This estimation is important for understanding how the mechanical properties of the human ankle are modulated during locomotion, and how those properties can be replicated in artificial prostheses designed to restore natural movement control. Here, we introduce a mechatronic platform designed to address the challenge of estimating the stiffness component of ankle impedance during walking, where stiffness denotes the static component of impedance. The system consists of a single degree of freedom mechatronic platform that is capable of perturbing the ankle during the stance phase of walking and measuring the response torque. Additionally, we estimate the platform's intrinsic inertial impedance using parallel linear filters and present a set of methods for estimating the impedance of the ankle from walking data. The methods were validated by comparing the experimentally determined estimates for the stiffness of a prosthetic foot to those measured from an independent testing machine. The parallel filters accurately estimated the mechatronic platform's inertial impedance, accounting for 96% of the variance, when averaged across channels and trials. Furthermore, our measurement system was found to yield reliable estimates of stiffness, which had an average error of only 5.4% (standard deviation: 0.7%) when measured at three time points within the stance phase of locomotion, and compared to the independently determined stiffness values of the prosthetic foot. The mechatronic system and methods proposed in this study are capable of accurately estimating ankle stiffness during the foot-flat region of stance phase. Future work will focus on the implementation of this validated system in estimating human ankle impedance during the stance phase of walking.

Non-weight-bearing neural control of a powered transfemoral prosthesis.

Lower limb prostheses have traditionally been mechanically passive devices without electronic control systems. Microprocessor-controlled passive and powered devices have recently received much interest from the clinical and research communities. The control systems for these devices typically use finite-state controllers to interpret data measured from mechanical sensors embedded within the prosthesis. In this paper we investigated a control system that relied on information extracted from myoelectric signals to control a lower limb prosthesis while amputee patients were seated. Sagittal plane motions of the knee and ankle can be accurately (>90%) recognized and controlled in both a virtual environment and on an actuated transfemoral prosthesis using only myoelectric signals measured from nine residual thigh muscles. Patients also demonstrated accurate (~90%) control of both the femoral and tibial rotation degrees of freedom within the virtual environment. A channel subset investigation was completed and the results showed that only five residual thigh muscles are required to achieve accurate control. This research is the first step in our long-term goal of implementing myoelectric control of lower limb prostheses during both weight-bearing and non-weight-bearing activities for individuals with transfemoral amputation.

User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use.

With the increasing availability of more advanced prostheses individuals with a transradial amputation can now be fit with single to multi-degree of freedom hands. Reliable and accurate control of these multi-grip hands still remains challenging. This is the first multi-user study to investigate at-home control and use of a multi-grip hand prosthesis under pattern recognition and direct control. Individuals with a transradial amputation were fitted with and trained to use an OSSUR i-Limb Ultra Revolution with Coapt COMPLETE CONTROL system. They participated in two 8-week home trials using the hand under myoelectric direct and pattern recognition control in a randomized order. While at home, participants demonstrated broader usage of grips in pattern recognition compared to direct control. After the home trial, they showed significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control; other outcome measures showed no differences between control styles. Additionally, this study provided a unique opportunity to evaluate EMG signals during home use. Offline analysis of calibration data showed that users were 81.5% [7.1] accurate across a range of three to five grips. Although EMG signal noise was identified during some calibrations, overall EMG quality was sufficient to provide users with control performance at or better than direct control.

Myoelectric prosthesis hand grasp control following targeted muscle reinnervation in individuals with transradial amputation.

BACKGROUND: Despite the growing availability of multifunctional prosthetic hands, users' control and overall functional abilities with these hands remain limited. The combination of pattern recognition control and targeted muscle reinnervation (TMR) surgery, an innovative technique where amputated nerves are transferred to reinnervate new muscle targets in the residual limb, has been used to improve prosthesis control of individuals with more proximal upper limb amputations (i.e., shoulder disarticulation and transhumeral amputation). OBJECTIVE: The goal of this study was to determine if prosthesis hand grasp control improves following transradial TMR surgery. METHODS: Eight participants were trained to use a multi-articulating hand prosthesis under myoelectric pattern recognition control. All participated in home usage trials pre- and post-TMR surgery. Upper limb outcome measures were collected following each home trial. RESULTS: Three outcome measures (Southampton Hand Assessment Procedure, Jebsen-Taylor Hand Function Test, and Box and Blocks Test) improved 9-12 months post-TMR surgery compared with pre-surgery measures. The Assessment of Capacity for Myoelectric Control and Activities Measure for Upper Limb Amputees outcome measures had no difference pre- and post-surgery. An offline electromyography analysis showed a decrease in grip classification error post-TMR surgery compared to pre-TMR surgery. Additionally, a majority of subjects noted qualitative improvements in their residual limb and phantom limb sensations post-TMR. CONCLUSIONS: The potential for TMR surgery to result in more repeatable muscle contractions, possibly due to the reduction in pain levels and/or changes to phantom limb sensations, may increase functional use of many of the clinically available dexterous prosthetic hands.

Toward higher-performance bionic limbs for wider clinical use.

Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.