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.

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.

A novel, low-cost transradial socket fabrication method using mass-producible components and expanding rigid foam.

Background: Millions of people in low- and middle-income countries lack access to prosthetic care. A well-fitting, durable socket is important for prosthesis comfort and function, but conventional fabrication techniques require highly trained clinicians and specialized equipment.

Objectives: To increase access to prosthetic care by developing a simple, low-cost socket fabrication method that does not require specialized equipment or electricity, and can be performed by persons with minimal prosthetic training.

Pattern recognition and direct control home use of a multi-articulating hand prosthesis.

Although more multi-articulating hand prostheses have become commercially available, replacing a missing hand remains challenging from a control perspective. This study investigated myoelectric direct control and pattern recognition home use of a multi-articulating hand prosthesis for individuals with a transradial amputation. Four participants were fitted with an i-limb Ultra Revolution hand and a Coapt COMPLETE CONTROL system.

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.

Innovative Use of Thighplasty to Improve Prosthesis Fit and Function in a Transfemoral Amputee.

Background: Excess residual limb fat is a common problem that can impair prosthesis control and negatively impact gait. In the general population, thighplasty and liposuction are commonly performed for cosmetic reasons but not specifically to improve function in amputees. The objective of this study was to determine if these procedures could enhance prosthesis fit and function in an overweight above-knee amputee.

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.

Myoelectric Pattern Recognition Outperforms Direct Control for Transhumeral Amputees with Targeted Muscle Reinnervation: A Randomized Clinical Trial.

Recently commercialized powered prosthetic arm systems hold great potential in restoring function for people with upper-limb loss. However, effective use of such devices remains limited by conventional (direct) control methods, which rely on electromyographic signals produced from a limited set of muscles. Targeted Muscle Reinnervation (TMR) is a nerve transfer procedure that creates additional recording sites for myoelectric prosthesis control.

A lightweight robotic ankle prosthesis with non-backdrivable cam-based transmission.

Below-knee level amputation significantly impacts the ability of an individual to ambulate. Transtibial amputees are typically prescribed energetically passive ankle-foot prostheses that behave as a spring or controlled damper, and therefore cannot fully replace the function of the missing limb. More recently, fully-powered devices have been proposed to more closely match the power generation ability of intact limbs.

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.

A Comparison of Pattern Recognition Control and Direct Control of a Multiple Degree-of-Freedom Transradial Prosthesis.

With existing conventional prosthesis control (direct control), individuals with a transradial amputation use two opposing muscle groups to control each prosthesis motor. As component complexity increases, subjects must switch the prosthesis into different modes to control each component in sequence. Pattern recognition control offers the ability to control multiple movements in a seamless manner without switching.

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.

Novel intramedullary device for lengthening transfemoral residual limbs.

Background: Lower limb loss is a highly disabling medical condition that can severely impact a person's quality of life. Recovery becomes especially challenging if an amputee has a short residual limb, which can complicate proper prosthetic fitting, causing discomfort, difficulties in suspension, and reduced mobility. Current limb lengthening techniques such as the Ilizarov apparatus and external fixators are cumbersome, uncomfortable, and have high complication rates.

Evaluating EMG Feature and Classifier Selection for Application to Partial-Hand Prosthesis Control.

Pattern recognition-based myoelectric control of upper-limb prostheses has the potential to restore control of multiple degrees of freedom. Though this control method has been extensively studied in individuals with higher-level amputations, few studies have investigated its effectiveness for individuals with partial-hand amputations. Most partial-hand amputees retain a functional wrist and the ability of pattern recognition-based methods to correctly classify hand motions from different wrist positions is not well studied.

Dual Window Pattern Recognition Classifier for Improved Partial-Hand Prosthesis Control.

Although partial-hand amputees largely retain the ability to use their wrist, it is difficult to preserve wrist motion while using a myoelectric partial-hand prosthesis without severely impacting control performance. Electromyogram (EMG) pattern recognition is a well-studied control method; however, EMG from wrist motion can obscure myoelectric finger control signals. Thus, to accommodate wrist motion and to provide high classification accuracy and minimize system latency, we developed a training protocol and a classifier that switches between long and short EMG analysis window lengths.

Anticipatory kinematics and muscle activity preceding transitions from level-ground walking to stair ascent and descent.

The majority of fall-related accidents are during stair ambulation-occurring commonly at the top and bottom stairs of each flight, locations in which individuals are transitioning to stairs. Little is known about how individuals adjust their biomechanics in anticipation of walking-stair transitions. We identified the anticipatory stride mechanics of nine able-bodied individuals as they approached transitions from level ground walking to stair ascent and descent.

Real-time simultaneous myoelectric control by transradial amputees using linear and probability-weighted regression.

Regression-based prosthesis control using surface electromyography (EMG) has demonstrated real-time simultaneous control of multiple degrees of freedom (DOFs) in transradial amputees. However, these systems have been limited to control of wrist DOFs. Use of intramuscular EMG has shown promise for both wrist and hand control in able-bodied subjects, but to date has not been evaluated in amputee subjects.

Use of probabilistic weights to enhance linear regression myoelectric control.

Objective: Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control.

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.

Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

Goal: The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees.

Methods: Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control.

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.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees.

Myoelectric Control System and Task-Specific Characteristics Affect Voluntary Use of Simultaneous Control.

Clinically available myoelectric control does not enable simultaneous proportional control of prosthetic degrees of freedom. Multiple studies have proposed systems that provide simultaneous control, though few have investigated whether subjects voluntarily use simultaneous control or how they implement it. Additionally, few studies have explicitly evaluated the effect of providing proportional velocity control.

Targeted muscle reinnervation and advanced prosthetic arms.

Targeted muscle reinnervation (TMR) is a surgical procedure used to improve the control of upper limb prostheses. Residual nerves from the amputated limb are transferred to reinnervate new muscle targets that have otherwise lost their function. These reinnervated muscles then serve as biological amplifiers of the amputated nerve motor signals, allowing for more intuitive control of advanced prosthetic arms.

Recovery strategy identification throughout swing phase using kinematic data from the tripped leg.

Falls are a large concern for individuals with lower limb amputations. Advanced powered prosthetic devices have the potential to quickly intervene after perturbations and help avoid a fall, but active balance recovery mechanisms have yet to be implemented. We investigated the feasibility of a realtime pattern recognition system for identification of trip recovery strategies.