Sibylle B. Thies

Falls and gait characteristics among older persons with peripheral neuropathy

DeMott TK, Richardson JK, Thies SB, Ashton-Miller JA: Falls and gait characteristics among older persons with peripheral neuropathy. Am J Phys Med Rehabil 2007;86:125–132. Objective:To prospectively determine the frequency and circumstances of falls in older persons with peripheral neuropathy and to identify gait characteristics on smooth and irregular surfaces associated with falls in this same population. Design:This was a descriptive and observational study of a prospective group cohort. Spatial and temporal gait measures on smooth and irregular surfaces, as well as basic demographic and clinical data, were obtained in 20 older persons with peripheral neuropathy. Falls and fall-related injuries were then prospectively determined for 1 yr. Results:Thirteen of 20 (65%) subjects fell, and 6 of 20 (30%) subjects sustained a fall-related injury during the year of observation. Of the 76 reported falls, 69 (90.8%) were associated with a surface abnormality (irregular or slick). Gait measures on the smooth surface did not distinguish between fall groups. On the irregular surface, however, step-time variability tended to be higher for those subjects who fell than for those who did not (89 ± 29 vs. 64 ± 26 msecs, respectively; P = 0.077) and for those who were injured from a fall compared with those who were not injured (101 ± 21 vs. 71 ± 29 msecs, respectively; P = 0.038). Conclusions:Older patients with peripheral neuropathy have a high rate of falls, and these falls are often associated with walking on irregular surfaces. Gait analysis on an irregular surface may be superior to that on a smooth surface for detecting fall risk in this patient population.

A Comparison of Gait Characteristics Between Older Women with and Without Peripheral Neuropathy in Standard and Challenging Environments

Objectives: To compare gait patterns in older women with and without peripheral neuropathy (PN) in standard (smooth surface, normal lighting) and challenging environments (CE) (irregular surface, low lighting).

Interventions improve gait regularity in patients with peripheral neuropathy while walking on an irregular surface under low light

Objectives: To determine which, if any, of three inexpensive interventions improve gait regularity in patients with peripheral neuropathy (PN) while walking on an irregular surface under low‐light conditions.

A comparison of gait characteristics between older women with and without peripheral neuropathy on smooth and unlevel surfaces

Objectives: To compare gait patterns in older women with and without peripheral neuropathy (PN) in standard (smooth surface, normal lighting) and challenging environments (CE) (irregular surface, low lighting).

Automated Detection of Instantaneous Gait Events Using Time Frequency Analysis and Manifold Embedding

Accelerometry is a widely used sensing modality in human biomechanics due to its portability, non-invasiveness, and accuracy. However, difficulties lie in signal variability and interpretation in relation to biomechanical events. In walking, heel strike and toe off are primary gait events where robust and accurate detection is essential for gait-related applications. This paper describes a novel and generic event detection algorithm applicable to signals from tri-axial accelerometers placed on the foot, ankle, shank or waist. Data from healthy subjects undergoing multiple walking trials on flat and inclined, as well as smooth and tactile paving surfaces is acquired for experimentation. The benchmark timings at which heel strike and toe off occur, are determined using kinematic data recorded from a motion capture system. The algorithm extracts features from each of the acceleration signals using a continuous wavelet transform over a wide range of scales. A locality preserving embedding method is then applied to reduce the high dimensionality caused by the multiple scales while preserving salient features for classification. A simple Gaussian mixture model is then trained to classify each of the time samples into heel strike, toe off or no event categories. Results show good detection and temporal accuracies for different sensor locations and different walking terrains.

Visuomotor behaviours when using a myoelectric prosthesis.

BackgroundA recent study showed that the gaze patterns of amputee users of myoelectric prostheses differ markedly from those seen in anatomically intact subjects. Gaze behaviour is a promising outcome measures for prosthesis designers, as it appears to reflect the strategies adopted by amputees to compensate for the absence of proprioceptive feedback and uncertainty/delays in the control system, factors believed to be central to the difficulty in using prostheses. The primary aim of our study was to characterise visuomotor behaviours over learning to use a trans-radial myoelectric prosthesis. Secondly, as there are logistical advantages to using anatomically intact subjects in prosthesis evaluation studies, we investigated similarities in visuomotor behaviours between anatomically intact users of a trans-radial prosthesis simulator and experienced trans-radial myoelectric prosthesis users.MethodsIn part 1 of the study, we investigated visuomotor behaviours during performance of a functional task (reaching, grasping and manipulating a carton) in a group of seven anatomically intact subjects over learning to use a trans-radial myoelectric prosthesis simulator (Dataset 1). Secondly, we compared their patterns of visuomotor behaviour with those of four experienced trans-radial myoelectric prosthesis users (Dataset 2). We recorded task movement time, performance on the SHAP test of hand function and gaze behaviour.ResultsDataset 1 showed that while reaching and grasping the object, anatomically intact subjects using the prosthesis simulator devoted around 90% of their visual attention to either the hand or the area of the object to be grasped. This pattern of behaviour did not change with training, and similar patterns were seen in Dataset 2. Anatomically intact subjects exhibited significant increases in task duration at their first attempts to use the prosthesis simulator. At the end of training, the values had decreased and were similar to those seen in Dataset 2.ConclusionsThe study provides the first functional description of the gaze behaviours seen during use of a myoelectric prosthesis. Gaze behaviours were found to be relatively insensitive to practice. In addition, encouraging similarities were seen between the amputee group and the prosthesis simulator group.

An Instance-Based Algorithm With Auxiliary Similarity Information for the Estimation of Gait Kinematics From Wearable Sensors

Wearable human movement measurement systems are increasingly popular as a means of capturing human movement data in real-world situations. Previous work has attempted to estimate segment kinematics during walking from foot acceleration and angular velocity data. In this paper, we propose a novel neural network [GRNN with Auxiliary Similarity Information (GASI)] that estimates joint kinematics by taking account of proximity and gait trajectory slope information through adaptive weighting. Furthermore, multiple kernel bandwidth parameters are used that can adapt to the local data density. To demonstrate the value of the GASI algorithm, hip, knee, and ankle joint motions are estimated from acceleration and angular velocity data for the foot and shank, collected using commercially available wearable sensors. Reference hip, knee, and ankle kinematic data were obtained using externally mounted reflective markers and infrared cameras for subjects while they walked at different speeds. The results provide further evidence that a neural net approach to the estimation of joint kinematics is feasible and shows promise, but other practical issues must be addressed before this approach is mature enough for clinical implementation. Furthermore, they demonstrate the utility of the new GASI algorithm for making estimates from continuous periodic data that include noise and a significant level of variability.

Effects of ramp negotiation, paving type and shoe sole geometry on toe clearance in young adults

Trips are a major cause of falls and result from involuntary contact of the foot with the ground during the swing phase of gait. Adequate toe clearance during swing is therefore crucial for safe locomotion. To date, little is known about the effects of environmental factors and footwear on toe clearance. This study reports on modulation of toe clearance and toe clearance variability in response to changes in ground inclination, paving type, and shoe sole geometry. Toe clearance and toe clearance variability for ten healthy young adults were calculated two-fold: a) for the commonly-used position on the foremost part of the sole of the shoe and b) for the lowest of a total of 7 sole positions, located between the metatarsals and the toe tip across the entire width of the sole. Utilizing a full-factorial design we found that toe clearance was affected by ground inclination, paving type, and sole geometry regardless of the computational method used (with p-values<0.01) but the use of the foremost part of the sole for toe clearance calculation results is an overestimation of this value. Our findings highlight the importance of considering footwear and environmental factors when assessing the risk of tripping. Future work needs to investigate to which extent the same factors affect toe clearance in more vulnerable parts of the population.

Artificial neural network prediction using accelerometers to control upper limb FES during reaching and grasping following stroke.

This work investigates arm acceleration as a control signal for functional electrical stimulation (FES) of the upper limb during reaching and grasping. We segment the reach and grasp motion into phases and present an artificial neural network (ANN) approach that estimates the phase of the reaching cycle from accelerometer signals. We then select the stimulator command that maximizes successful triggering without unnecessary risk to the patients safety. Our results suggest that the algorithm successfully generalizes between sessions and patients but is less successful at generalizing between different motions

The Reality of Myoelectric Prostheses: Understanding What Makes These Devices Difficult for Some Users to Control

Users of myoelectric prostheses can often find them difficult to control. This can lead to passive-use of the device or total rejection, which can have detrimental effects on the contralateral limb due to overuse. Current clinically available prostheses are “open loop” systems, and although considerable effort has been focused on developing biofeedback to “close the loop,” there is evidence from laboratory-based studies that other factors, notably improving predictability of response, may be as, if not more, important. Interestingly, despite a large volume of research aimed at improving myoelectric prostheses, it is not currently known which aspect of clinically available systems has the greatest impact on overall functionality and everyday usage. A protocol has, therefore, been designed to assess electromyographic (EMG) skill of the user and predictability of the prosthesis response as significant parts of the control chain, and to relate these to functionality and everyday usage. Here, we present the protocol and results from early pilot work. A set of experiments has been developed. First, to characterize user skill in generating the required level of EMG signal, as well as the speed with which users are able to make the decision to activate the appropriate muscles. Second, to measure unpredictability introduced at the skin–electrode interface, in order to understand the effects of the socket-mounted electrode fit under different loads on the variability of time taken for the prosthetic hand to respond. To evaluate prosthesis user functionality, four different outcome measures are assessed. Using a simple upper limb functional task prosthesis users are assessed for (1) success of task completion, (2) task duration, (3) quality of movement, and (4) gaze behavior. To evaluate everyday usage away from the clinic, the symmetricity of their real-world arm use is assessed using activity monitoring. These methods will later be used to assess a prosthesis user cohort to establish the relative contribution of each control factor to the individual measures of functionality and everyday usage (using multiple regression models). The results will support future researchers, designers, and clinicians in concentrating their efforts on the area that will have the greatest impact on improving prosthesis use.