For the upgrade of its Inner Tracking System, the ALICE experiment plans to install a new tracker fully constructed with monolithic active pixel sensors implemented in a standard 180 nm CMOS imaging ...sensor process, with a deep pwell allowing full CMOS within the pixel. Reverse substrate bias increases the tolerance to non-ionizing energy loss (NIEL) well beyond 10131MeVneq∕cm2, but does not allow full depletion of the sensitive layer and hence full charge collection by drift, mandatory for more extreme radiation tolerance. This paper describes a process modification to fully deplete the epitaxial layer even with a small charge collection electrode. It uses a low dose blanket deep high energy n-type implant in the pixel array and does not require significant circuit or layout changes so that the same design can be fabricated both in the standard and modified process. When exposed to a 55Fe source at a reverse substrate bias of −6 V, pixels implemented in the standard and the modified process in a low and high dose variant for the deep n-type implant respectively yield a signal of about 115 mV, 110 mV and 90 mV at the output of a follower circuit. Signal rise times heavily affected by the speed of this circuit are 27.8+∕−5 ns, 23.2+∕−4.2 ns, and 22.2+∕−3.7 ns rms, respectively. In a different setup, the single pixel signal from a 90Sr source only degrades by less than 20% for the modified process after a 10151MeVneq∕cm2 irradiation, while the signal rise time only degrades by about 16+∕−2 ns to 19+∕−2.8 ns rms. From sensors implemented in the standard process no useful signal could be extracted after the same exposure. These first results indicate the process modification maintains low sensor capacitance, improves timing performance and increases NIEL tolerance by at least an order of magnitude.
Injury or disease often compromise walking dynamics and negatively impact quality of life and independence. Assessing methods to restore or improve pathological gait can be expedited by examining a ...global parameter that reflects overall musculoskeletal control. Center of mass (CoM) kinematics follow well-defined trajectories during unimpaired gait, and change predictably with various gait pathologies. We propose a method to estimate CoM trajectories from inertial measurement units (IMUs) using a bidirectional Long Short-Term Memory neural network to evaluate rehabilitation interventions and outcomes. Five able-bodied volunteers participated in a single session of various dynamic walking trials with IMUs mounted on various body segments. A neural network trained with data from four of the five volunteers through a leave-one-subject out cross validation estimated the CoM with average root mean square errors (RMSEs) of 1.44cm, 1.15cm, and 0.40cm in the mediolateral (ML), anteroposterior (AP), and inferior/superior (IS) directions respectively. The impact of number and location of IMUs on network prediction accuracy was determined via principal component analysis. Comparing across all configurations, three to five IMUs located on the legs and medial trunk were the most promising reduced sensor sets for achieving CoM estimates suitable for outcome assessment. Lastly, the networks were tested on data from an individual with hemiparesis with the greatest error increase in the ML direction, which could stem from asymmetric gait. These results provide a framework for assessing gait deviations after disease or injury and evaluating rehabilitation interventions intended to normalize gait pathologies.
To determine the stimulated strength of the paralyzed gluteal and paraspinal muscles and their effects on the seated function of individuals with paralysis.
Case series with subjects acting as their ...own concurrent controls.
Hospital-based clinical biomechanics laboratory.
Users (N=8) of implanted neuroprostheses for lower extremity function with low-cervical or thoracic level injuries.
Dynamometry and digital motion capture both with and without stimulation to the hip and trunk muscles.
Isometric trunk extension moment at 0°, 15°, and 30° of flexion; seated stability in terms of simulated isokinetic rowing; pelvic tilt, shoulder height, loaded and unloaded bimanual reaching to different heights, and subjective ratings of difficulty during unsupported sitting.
Stimulation produced significant increases in mean trunk extension moment (9.2±9.5Nm, P<.001) and rowing force (27.4±23.1N, P<.012) over baseline volitional values. Similarly, stimulation induced positive changes in average pelvic tilt (16.7±15.7°) and shoulder height (2.2±2.5cm) during quiet sitting and bimanual reaching, and increased mean reach distance (5.5±6.6cm) over all subjects, target heights, and loading conditions. Subjects consistently rated tasks with stimulation easier than voluntary effort alone.
In spite of considerable intersubject variability, stabilizing the paralyzed trunk with electrical stimulation can positively impact seated posture, extend forward reach, and allow exertion of larger forces on objects in the environment.
Feedback control of functional neuromuscular stimulation has the potential to improve daily function for individuals with spinal cord injuries (SCIs) by enhancing seated stability. Our fully ...implanted networked neuroprosthesis (NNP) can provide real-time feedback signals for controlling the trunk through accelerometers embedded in modules distributed throughout the trunk. Typically, inertial sensors are aligned with the relevant body segment. However, NNP implanted modules are placed according to surgical constraints and their precise locations and orientations are generally unknown. We have developed a method for calibrating multiple randomly oriented accelerometers and fusing their signals into a measure of trunk orientation. Six accelerometers were externally attached in random orientations to the trunks of six individuals with SCI. Calibration with an optical motion capture system resulted in RMSE below 5° and correlation coefficients above 0.97. Calibration with a handheld goniometer resulted in RMSE of 7° and correlation coefficients above 0.93. Our method can obtain trunk orientation from a network of sensors without
knowledge of their relationships to the body anatomical axes. The results of this study will be invaluable in the design of feedback control systems for stabilizing the trunk of individuals with SCI in combination with the NNP implanted technology.
For individuals with spinal cord injuries (SCIs) above the midthoracic level, a common complication is the partial or complete loss of trunk stability in the seated position. Functional neuromuscular ...stimulation (FNS) can restore seated posture and other motor functions after paralysis by applying small electrical currents to the peripheral motor nerves. In particular, the Networked Neuroprosthesis (NNP) is a fully implanted, modular FNS system that is also capable of capturing information from embedded accelerometers for measuring trunk tilt for feedback control of stimulation. The NNP modules containing the accelerometers are located in the body based on surgical constraints. As such, their exact orientations are generally unknown and cannot be easily assessed. In this study, a method for estimating trunk tilt that employed the Gram–Schmidt method to reorient acceleration signals to the anatomical axes of the body was developed and deployed in individuals with SCI using the implanted NNP system. An anatomically realistic model of a human trunk and five accelerometer sensors was developed to verify the accuracy of the reorientation algorithm. Correlation coefficients and root mean square errors (RMSEs) were calculated to compare target trunk tilt estimates and tilt estimates derived from simulated accelerometer signals under a variety of conditions. Simulated trunk tilt estimates with correlation coefficients above 0.92 and RMSEs below 5° were achieved. The algorithm was then applied to accelerometer signals from implanted sensors installed in three NNP recipients. Error analysis was performed by comparing the correlation coefficients and RMSEs derived from trunk tilt estimates calculated from implanted sensor signals to those calculated via motion capture data, which served as the gold standard. NNP-derived trunk tilt estimates exhibited correlation coefficients between 0.80 and 0.95 and RMSEs below 13° for both pitch and roll in most cases. These findings suggest that the algorithm is effective at estimating trunk tilt with the implanted sensors of the NNP system, which implies that the method may be appropriate for extracting feedback signals for control systems for seated stability with NNP technology for individuals who have reduced control of their trunk due to paralysis.
Functional electrical stimulation and spinal cord injury Ho, Chester H; Triolo, Ronald J; Elias, Anastasia L ...
Physical medicine and rehabilitation clinics of North America,
08/2014, Letnik:
25, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Spinal cord injuries (SCI) can disrupt communications between the brain and the body, resulting in loss of control over otherwise intact neuromuscular systems. Functional electrical stimulation (FES) ...of the central and peripheral nervous system can use these intact neuromuscular systems to provide therapeutic exercise options to allow functional restoration and to manage medical complications following SCI. The use of FES for the restoration of muscular and organ functions may significantly decrease the morbidity and mortality following SCI. Many FES devices are commercially available and should be considered as part of the lifelong rehabilitation care plan for all eligible persons with SCI.
The trunk movements of an individual paralyzed by spinal cord injury (SCI) can be restored by functional neuromuscular stimulation (FNS), which applies low-level current to the motor nerves to ...activate the paralyzed muscles to generate useful torques, to actuate the trunk. FNS can be modulated to vary the biotorques to drive the trunk to follow a user-defined reference motion and maintain it at a desired postural set-point. However, a stabilizing modulation policy (i.e., control law) is difficult to derive as the biomechanics of the spine and pelvis are complex and the neuromuscular dynamics are highly nonlinear, nonautonomous, and input redundant. Therefore, a control method that can stabilize it with FNS without knowing the accurate skeletal and neuromuscular dynamics is desired. To achieve this goal, we propose a control framework consisting of a robust control module that generates stabilizing torques while an artificial neural network-based mapping mechanism with an anatomy-based updating law ensures that the muscle-generated torques converge to the stabilizing values. For the robust control module, two sliding-mode robust controllers (i.e., a high compensation controller and an adaptive controller), were investigated. System stability of the proposed control method was rigorously analyzed based on the assumption that the skeletal dynamics can be approximated by Euler-Lagrange equations with bounded disturbances, which enables the generalization of the control framework. We present experiments in a simulation environment where an anatomically realistic three-dimensional musculoskeletal model of the human trunk moved in the anterior- posterior and medial-lateral directions while perturbations were applied. The satisfactory simulation results suggest the potential of this control technique for trunk tracking tasks in a typical clinical environment.
Restoring or improving seated stability after spinal cord injury (SCI) can improve the ability to perform activities of daily living by providing a dynamic, yet stable, base for upper extremity ...motion. Seated stability can be obtained with activation of the otherwise paralyzed trunk and hip musculature with neural stimulation, which has been shown to extend upper limb reach and improve seated posture.
We implemented a proportional, integral, derivative (PID) controller to maintain upright seated posture by simultaneously modulating both forward flexion and lateral bending with functional neuromuscular stimulation. The controller was tested with a functional reaching task meant to require trunk movements and impart internal perturbations through rapid changes in inertia due to acquiring, moving, and replacing objects with one upper extremity. Five subjects with SCI at various injury levels who had received implanted stimulators targeting their trunk and hip muscles participated in the study. Each subject was asked to move a weighted jar radially from a center home station to one of three target stations. The task was performed with the controller active, inactive, or with a constant low level of neural stimulation. Trunk pitch (flexion) and roll (lateral bending) angles were measured with motion capture and plotted against each other to generate elliptical movement profiles for each task and condition. Postural sway was quantified by calculating the ellipse area. Additionally, the mean effective reach (distance between the shoulder and wrist) and the time required to return to an upright posture was determined during reaching movements.
Postural sway was reduced by the controller in two of the subjects, and mean effective reach was increased in three subjects and decreased for one. Analysis of the major direction of motion showed return to upright movements were quickened by 0.17 to 0.32 s. A 15 to 25% improvement over low/no stimulation was observed for four subjects.
These results suggest that feedback control of neural stimulation is a viable way to maintain upright seated posture by facilitating trunk movements necessary to complete reaching tasks in individuals with SCI. Replication of these findings on a larger number of subjects would be necessary for generalization to the various segments of the SCI population.
Paralysis of the trunk results in seated instability leading to difficulties performing activities of daily living. Functional neuromuscular stimulation (FNS) combined with control systems have the ...potential to restore some dynamic functions of the trunk. However, design of multi-joint, multi-muscle control systems requires characterization of the stimulation-driven muscles responsible for movement. Objective: This study characterizes the input-output properties of paralyzed trunk muscles activated by FNS, and explores co-activation of muscles. Methods: Four participants with various spinal cord injuries (C7 AIS-B, T4 AIS-B, T5 AIS-A, C5 AIS-C) were constrained so lumbar forces were transmitted to a load cell while an implanted neuroprosthesis activated otherwise paralyzed hip and paraspinal muscles. Isometric force recruitment curves in the nominal seated position were generated by inputting the level of stimulation (pulse width modulation) while measuring the resulting muscle force. Two participants returned for a second experiment where muscles were co-activated to determine if their actions combined linearly. Results: Recruitment curves of most trunk and hip muscles fit sigmoid shaped curves with a regression coefficient above 0.75, and co-activation of the muscles combined linearly across the hip and lumbar joint. Subject specific perturbation plots showed one subject is capable of resisting up to a 300N perturbation anteriorly and 125N laterally; with some subjects falling considerably below these values. Conclusion: Development of a trunk stability control system can use sigmoid recruitment dynamics and assume muscle forces combine linearly. Significance: This study informs future designs of multi-muscle, and multi-dimensional FNS systems to maintain seated posture and stability.
A two-part simulation process was developed to investigate the facilitation of vertical patient lifts with functional neuromuscular stimulation (FNS) in individuals with spinal cord injury (SCI). ...First, external lifting forces representing caregiver assistance were applied to a 3D musculoskeletal model representing the patient and optimized to enforce a specific lifting trajectory during a forward dynamic simulation. The process was repeated with and without the activation of the knee, hip, and trunk extensor muscles of the patient model to represent contractions of the paralyzed muscles generated via FNS. Secondly, the spinal compression experienced by a caregiver at the L5/S1 joint while generating these external lifting forces was estimated using a second musculoskeletal model representing the caregiver. Simulation without muscle activation predicted spinal compression in the caregiver model approximately 1.3 × the National Institute for Occupational Safety and Health (NIOSH) recommended “Action Limit.” Comparatively, simulations with two unique patterns of muscle activation both predicted caregiver spinal compressions below NIOSH recommendations. These simulation results support the hypothesis that FNS activation of a patient’s otherwise paralyzed muscles would lower the force output required of a caregiver during a dependent transfer, thus lowering the spinal compression and risk of injury experienced by a caregiver.
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