New control strategies for neuroprosthetic systems

The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with\ud neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accomplish these tasks include feedforward (open-loop), feedback, and adaptive control. Feedforward control requires a great deal of information about the biomechanical behavior of the limb. For the upper extremity, an artificial motor program was developed to provide such movement program input to a neuroprosthesis. In lower extremity control, one group achieved their best results by attempting to meet naturally perceived gait objectives rather than to follow an exact joint angle trajectory. Adaptive feedforward control, as implemented in the cycleto-cycle controller, gave good compensation for the gradual decrease in performance observed with open-loop control. A neural network controller was able to control its system to customize stimulation parameters in order to generate a desired output trajectory in a given individual and to maintain tracking performance in the presence of muscle fatigue. The authors believe that practical FNS control systems must\ud exhibit many of these features of neurophysiological systems

Empowering and assisting natural human mobility: The simbiosis walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staf

Permutation entropy and irreversibility in gait kinematic time series from patients with mild cognitive decline and early alzheimer’s dementia

Gait is a basic cognitive purposeful action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. Herein, we report the results of a study of gait kinematic time series for two groups of patients (mild cognitive impairment and mild Alzheimer’s disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present in early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door to the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanismsThis research was funded through the Premio del Ilustre Colegio Profesional de Fisioterapeutas de la Comunidad De Madrid, prize number ICPFM-IX-201

Biomechanics for inclusive urban design : effects of tactile paving on older adults’ gait when crossing the street

In light of our ageing population it is important that the urban environment is easily accessible and hence supports older adults’ independence. Tactile ‘blister’ paving was originally designed to provide guidance for visually impaired people at pedestrian crossings. However, as research links irregular surfaces to falls in older adults, such paving may have an adverse effect on older people. We investigated the effects of tactile paving on older adults’ gait in a scenario closely resembling “crossing the street”. Gait analysis of 32 healthy older adults showed that tactile, as compared to smooth, paving increases the variability in timing of foot placement by 20%, thereby indicating a disturbance of the rhythmic gait pattern. Moreover, toe-clearance during the swing phase increased by 7% on tactile paving, and the ability to stop upon cue from the traffic light was compromised. These results need to be viewed under consideration of the limitations associated with laboratory studies and real world analysis is needed to fully understand their implications for urban design

Kinematic discrimination of ataxia in horses is facilitated by blindfolding

BACKGROUND: Agreement among experienced clinicians is poor when assessing the presence and severity of ataxia, especially when signs are mild. Consequently, objective gait measurements might be beneficial for assessment of horses with neurological diseases. OBJECTIVES: To assess diagnostic criteria using motion capture to measure variability in spatial gait-characteristics and swing duration derived from ataxic and non-ataxic horses, and to assess if variability increases with blindfolding. STUDY DESIGN: Cross-sectional. METHODS: A total of 21 horses underwent measurements in a gait laboratory and live neurological grading by multiple raters. In the gait laboratory, the horses were made to walk across a runway surrounded by a 12-camera motion capture system with a sample frequency of 240 Hz. They were made to walk normally and with a blindfold in at least three trials each. Displacements of reflective markers on head, fetlock, hoof, fourth lumbar vertebra, tuber coxae and sacrum derived from three to four consecutive strides were processed and descriptive statistics, receiver operator characteristics (ROC) to determine the diagnostic sensitivity, specificity and area under the curve (AUC), and correlation between median ataxia grade and gait parameters were determined. RESULTS: For horses with a median ataxia grade ≥2, coefficient of variation for the location of maximum vertical displacement of pelvic and thoracic distal limbs generated good diagnostic yield. The hoofs of the thoracic limbs yielded an AUC of 0.81 with 64% sensitivity and 90% specificity. Blindfolding exacerbated the variation for ataxic horses compared to non-ataxic horses with the hoof marker having an AUC of 0.89 with 82% sensitivity and 90% specificity. MAIN LIMITATIONS: The low number of consecutive strides per horse obtained with motion capture could decrease diagnostic utility. CONCLUSIONS: Motion capture can objectively aid the assessment of horses with ataxia. Furthermore, blindfolding increases variation in distal pelvic limb kinematics making it a useful clinical tool

Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling

In everyday life people use their mobile phones on-the-go with different walking speeds and with different touch input techniques. Unfortunately, much of the published research in mobile interaction does not quantify the influence of these variables. In this paper, we analyze the influence of walking speed, gait pattern and input techniques on commonly used performance parameters like error rate, accuracy and tapping speed, and we compare the results to the static condition. We examine the influence of these factors on the machine learned offset model used to correct user input and we make design recommendations. The results show that all performance parameters degraded when the subject started to move, for all input techniques. Index finger pointing techniques demonstrated overall better performance compared to thumb-pointing techniques. The influence of gait phase on tap event likelihood and accuracy was demonstrated for all input techniques and all walking speeds. Finally, it was shown that the offset model built on static data did not perform as well as models inferred from dynamic data, which indicates the speed-specific nature of the models. Also, models identified using specific input techniques did not perform well when tested in other conditions, demonstrating the limited validity of offset models to a particular input technique. The model was therefore calibrated using data recorded with the appropriate input technique, at 75% of preferred walking speed, which is the speed to which users spontaneously slow down when they use a mobile device and which presents a tradeoff between accuracy and usability. This led to an increase in accuracy compared to models built on static data. The error rate was reduced between 0.05% and 5.3% for landscape-based methods and between 5.3% and 11.9% for portrait-based methods

Fast Damage Recovery in Robotics with the T-Resilience Algorithm

Damage recovery is critical for autonomous robots that need to operate for a long time without assistance. Most current methods are complex and costly because they require anticipating each potential damage in order to have a contingency plan ready. As an alternative, we introduce the T-resilience algorithm, a new algorithm that allows robots to quickly and autonomously discover compensatory behaviors in unanticipated situations. This algorithm equips the robot with a self-model and discovers new behaviors by learning to avoid those that perform differently in the self-model and in reality. Our algorithm thus does not identify the damaged parts but it implicitly searches for efficient behaviors that do not use them. We evaluate the T-Resilience algorithm on a hexapod robot that needs to adapt to leg removal, broken legs and motor failures; we compare it to stochastic local search, policy gradient and the self-modeling algorithm proposed by Bongard et al. The behavior of the robot is assessed on-board thanks to a RGB-D sensor and a SLAM algorithm. Using only 25 tests on the robot and an overall running time of 20 minutes, T-Resilience consistently leads to substantially better results than the other approaches

Alterations in thoracolumbosacral movement when pain causing lameness has been improved by diagnostic analgesia

Lameness, thoracolumbosacral pain and reduced range of motion (ROM) often coexist; better understanding of their relationship is needed. The objectives were to determine if thoracolumbosacral movement of horses changes when pain causing lameness is improved by diagnostic analgesia. We hypothesised that reduction of lameness will increase ROM of the thoracolumbosacral region. Thirteen horses with different types of hind limb lameness were trotted in straight lines and lunged on a 10 m diameter circle on left and right reins before and after lameness was subjectively substantially improved by diagnostic analgesia. Inertial sensor data were collected from the withers, thirteenth (T13) and eighteenth thoracic (T18) vertebrae, third lumbar (13) vertebra, tubera sacrale (TS), left and right tubera coxae. ROM of flexion-extension, axial rotation, lateral bending, dorsoventral, lateral-lateral motion and vertical movement symmetry were quantified at each thoracolumbar site. Hiphike difference (HHD), maximum difference (MaxDiff) and minimum difference (MinDiff) for the pelvic sensors were measured. Percentage changes for before and after diagnostic analgesia were calculated; mean standard deviation (SD) or median [interquartile range] were determined. Associations between the change in pelvic versus thoracolumbar movement symmetry after each local analgesic technique were tested. After resolution of lameness, HHD decreased by 7% [68%] (P = 0.006). The MinDiff decreased significantly by 33%[61%] (P = 0.01), 45 +/- 13% (P = 0.005) and 52 +/- 23% (P = 0.04), for TS, L3 and T18, respectively. There was significantly increased ROM in flexion-extension at T13, in axial rotation at T13, T18, 13 and in lateral-lateral ROM at 13. Thoracolumbosacral asymmetry and reduced ROM associated with lameness were both altered immediately by improvement in lameness using diagnostic analgesia. (C) 2017 Elsevier Ltd. All rights reserved