This paper describes a control architecture and intent recognition approach for the real-time supervisory control of a powered lower limb prosthesis. The approach infers user intent to stand, sit, or walk, by recognizing patterns in prosthesis sensor data in real-time, without the need for instrumentation of the sound-side leg. Specifically, the intent recognizer utilizes time-based features extracted from frames of prosthesis signals, which are subsequently reduced to a lower dimensionality (for computational efficiency). These data are initially used to train intent models, which classify the patterns as standing, sitting, or walking. The trained models are subsequently used to infer the user's intent in real-time. In addition to describing the generalized control approach, this paper describes the implementation of this approach on a single unilateral transfemoral amputee subject, and demonstrates via experiments the effectiveness of the approach. In the real-time supervisory control experiments, the intent recognizer identified all 90 activity mode transitions, switching the underlying middle level controllers without any perceivable delay by the user. The intent recognizer also identified six activity mode transitions, which were not intended by the user. Due to the intentional overlapping functionality of the middle level controllers, the incorrect classifications neither caused problems in functionality, nor were perceived by the user.

This paper presents a self-contained powered knee and ankle prosthesis, intended to enhance the mobility of transfemoral amputees. A finite-state based impedance control approach, previously developed by the authors, is used for the control of the prosthesis during walking and standing. Experiments on an amputee subject for level treadmill and overground walking are described. Knee and ankle joint angle, torque, and power data taken during walking experiments at various speeds demonstrate the ability of the prosthesis to provide a functional gait that is representative of normal gait biomechanics. Measurements from the battery during level overground walking indicate that the self-contained device can provide more than 4500 strides, or 9 km, of walking at a speed of 5.1 km/ h between battery charges.

This paper extends a previously developed level- ground walking control methodology to enable an above knee amputee to walk up slopes using a powered knee and ankle prosthesis. Experimental results corresponding to walking on level ground and two different slope angles (5 (°) and 10 (°)) with the powered prosthesis using the control method are compared to walking under the same conditions with a passive prosthesis. The data indicate that the powered prosthesis with the upslope walking controller is able to reproduce several kinematic characteristics of healthy upslope walking that the passive prosthesis does not (such as knee flexion after heel strike and a powered ankle plantarflexion during push-off). Finally, results are shown that demonstrate the ability of the prosthesis to generate a slope estimate, which is in turn utilized to adapt the underlying control parameters to the corresponding slope.

Predictive models developed from off-the-shelf and EMR data using ML algorithms exceeded the treatment sensitivity and treatment specificity of clinicians. A prospective study is warranted to assess the clinical utility of the ML algorithms in improving the accuracy of antibiotic use in the management of neonatal sepsis.

This paper presents a method for providing volitional control of a powered knee prosthesis during nonweight-bearing activity such as sitting. The method utilizes an impedance framework, such that the joint can be programmed with a given stiffness and damping that reflects the nominal impedance properties of an intact joint. Volitional movement of the knee joint is commanded via the stiffness set-point angle of the joint impedance, which is commanded by the user as a function of the measured surface electromyogram (EMG) from the hamstring and quadriceps muscles of the residual limb. Rather than using the respective EMG measurements from these muscles to directly command the flexion or extension set point of the knee, the presented approach utilizes a combination of quadratic discriminant analysis and principal component analysis to align the user's intent to flex or extend the knee joint with the pattern of measured EMG. The approach was implemented on three transfemoral amputees, and their ability to control knee movement was characterized by a set of knee joint trajectory tracking tasks. Each amputee subject also performed the same set of trajectory tracking tasks with his sound side (intact) knee joint. The average root mean square trajectory tracking errors of the prosthetic knee employing the EMG-based volitional control and the intact knee of the three subjects were 6.2° and 5.2°, respectively.

This paper presents a finite state-based control system for a powered transfemoral prosthesis that provides stair ascent and descent capability. The control system was implemented on a powered prosthesis and evaluated by a unilateral, transfemoral amputee subject. The ability of the powered prosthesis to provide stair ascent and descent capability was assessed by comparing the gait kinematics, as recorded by a motion capture system, with the kinematics provided by a passive prosthesis, in addition to those recorded from a set of healthy subjects. The results indicate that the powered prosthesis provides gait kinematics that are considerably more representative of healthy gait, relative to the passive prosthesis, for both stair ascent and descent.

This paper presents an overview of the design and control of a fully self-contained prosthesis, which is intended to improve the mobility of transfemoral amputees. A finite-state based impedance control approach, previously developed by the authors, is used for the control of the prosthesis during walking and standing. The prosthesis was tested on an unilateral amputee subject for over-ground walking. Prosthesis sensor data (joint angles and torques) acquired during level ground walking experiments at a self-selected cadence demonstrates the ability of the device to provide a functional gait similar to normal gait biomechanics. Battery measurements during level ground walking experiments show that the self-contained device provides over 4,500 strides (9.0 km of walking at a speed of 5.1 km/h) between battery charges.

This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation.