Self-reported gait unsteadiness in mildly impaired neurological patients: an objective assessment through statistical gait analysis

Background Self-reported gait unsteadiness is often a problem in neurological patients without any clinical evidence of ataxia, because it leads to reduced activity and limitations in function. However, in the literature there are only a few papers that address this disorder. The aim of this study is to identify objectively subclinical abnormal gait strategies in these patients. Methods Eleven patients affected by self-reported unsteadiness during gait (4 TBI and 7 MS) and ten healthy subjects underwent gait analysis while walking back and forth on a 15-m long corridor. Time-distance parameters, ankle sagittal motion, and muscular activity during gait were acquired by a wearable gait analysis system (Step32, DemItalia, Italy) on a high number of successive strides in the same walk and statistically processed. Both self-selected gait speed and high speed were tested under relatively unconstrained conditions. Non-parametric statistical analysis (Mann-Whitney, Wilcoxon tests) was carried out on the means of the data of the two examined groups. Results The main findings, with data adjusted for velocity of progression, show that increased double support and reduced velocity of progression are the main parameters to discriminate patients with self-reported unsteadiness from healthy controls. Muscular intervals of activation showed a significant increase in the activity duration of the Rectus Femoris and Tibialis Anterior in patients with respect to the control group at high speed. Conclusions Patients with a subjective sensation of instability, not clinically documented, walk with altered strategies, especially at high gait speed. This is thought to depend on the mechanisms of postural control and coordination. The gait anomalies detected might explain the symptoms reported by the patients and allow for a more focused treatment design. The wearable gait analysis system used for long distance statistical walking assessment was able to detect subtle differences in functional performance monitoring, otherwise not detectable by common clinical examination

Straight-path and U-turn gait biomarkers in PD patients before and after deep-brain stimulation

Clinical gait analysis revealed that turnings are altered, even in the early stages of Parkinson’s Disease (PD), with increased turning arcs, time to complete the turn, and a larger number of steps taken to complete the turn. Furthermore, turning/curved walking is more likely to cause gait instabilities and increased variability compared to straight walking. Many studies focus on repeated trials of short intermittent walking bouts, while there is a lack of works considering continuous and prolonged overground walking, that includes both straight-path and turnings. However, this latest approach seems promising to obtain sensitive and reliable gait biomarkers recorded in ecological walking conditions. This study enrolled 20 PD patients and 20 healthy controls. PD patients were tested twice: before Deep-Brain-Stimulation (DBS) neurosurgery, and 3 months after it. All subjects were asked to walk for 5 minutes back and forth a straight path, and to U-turn for changing direction at the end of the 9-m walkway. Foot-floor contact events were directly detected by means of footswitches. Besides traditional gait parameters, the percentage of “non-standard” gait cycles was analyzed, i.e., cycles showing a sequence of foot-floor contact events different from the typical one (heel-strike/flat-foot-contact/push-off/swing), normalized with respect to the walking speed. Overall, PD patients considerably improved their gait after DBS. The percentage of “non-standard” gait cycles (also called “atypical” gait cycles) already proved to be an accurate biomarker for quantifying subtle gait dysfunctions in PD patients, correlated with the clinical score UPDRS-III. The present work demonstrated the validity of this parameter in the evaluation of the effects of the DBS, at 3 months after the implant. The segmentation of straight-path and U-turning epochs provided supplemental information, that can be useful in the management of PD patients. While the PD neuromuscular control after DBS was already analyzed in a recent work, this is the first contribution presenting original gait analysis data on this cohort of patients

Extension of the rigid‐constraint method for the heuristic suboptimal parameter tuning to ten sensor fusion algorithms using inertial and magnetic sensing

The orientation of a magneto‐inertial measurement unit can be estimated using a sensor fusion algorithm (SFA). However, orientation accuracy is greatly affected by the choice of the SFA parameter values which represents one of the most critical steps. A commonly adopted approach is to fine‐tune parameter values to minimize the difference between estimated and true orientation. However, this can only be implemented within the laboratory setting by requiring the use of a concurrent gold‐standard technology. To overcome this limitation, a Rigid‐Constraint Method (RCM) was proposed to estimate suboptimal parameter values without relying on any orientation reference. The RCM method effectiveness was successfully tested on a single‐parameter SFA, with an average error increase with respect to the optimal of 1.5 deg. In this work, the applicability of the RCM was evaluated on 10 popular SFAs with multiple parameters under different experimental scenarios. The average residual between the optimal and suboptimal errors amounted to 0.6 deg with a maximum of 3.7 deg. These encouraging results suggest the possibility to properly tune a generic SFA on different scenarios without using any reference. The synchronized dataset also including the optical data and the SFA codes are available online

Evaluation of time-series registration methods in dynamic area telethermometry for breast cancer detection

Automated motion reduction in 3D dynamic infrared imaging is on demand in many applications. Few methods for registering time-series dynamic infrared frames have been proposed. Almost all such methods are feature based algorithms requiring manual intervention. We apply different automated registration methods based on spatial displacement to 11 datasets of Breast Dynamic Infrared Imaging (DIRI) and evaluate the results in terms of both the image similarity and anatomical consistency of the transformation. The aim is to optimize the registration strategy for breast DIRI in order to improve the spectral analysis of temperature modulation; thus facilitating the acquisition procedure in a Dynamic Area Telethermometry framework. The results show that symmetric diffeomorphic demons registration outperforms both warped frames similarity and smoothness of deformation fields; hence proving effective for time-series dynamic infrared registration

Estimation of the base of support during gait with an unobtrusive wearable system

This study aimed at estimating the base of support (BoS) during gait with an unobtrusive wearable system. The BoS is the area identified by the points of contact of the body with the ground. During the double-support phase of gait both feet contribute to the BoS. The BoS is a measure of the subject’s balance. The estimation of the BoS outdoors is still an open issue. The innovative hardware presented here is a combination of a magneto-inertial measurement unit (MIMU) and two infrared time of flight (IR-ToF) sensors. The methods implemented to estimate the BoS were tested on a healthy subject and validated with a stereo-photogrammetric system. The results suggest that the solution proposed may be an effective and low-cost tool for the estimate of the BoS during gait in outdoor conditions

Muscle Synergy Assessment during Single-Leg Stance

In the study of muscle synergies during the maintenance of single-leg stance there are several methodological issues that must be taken into account before muscle synergy extraction. In particular, it is important to distinguish between epochs of surface electromyography (sEMG) signals corresponding to "well-balanced" and "unbalanced" single-leg stance, since different motor control strategies could be used to maintain balance. The aim of this work is to present and define a robust procedure to distinguish between "well-balanced" and "unbalanced" single-leg stance to be chosen as input for the algorithm used to extract muscle synergies. Our results demonstrate that the proposed approach for the selection of sEMG epochs relative to "well-balanced" and "unbalanced" single-leg stance is robust with respect to the selection of the segmentation threshold, revealing a high consistency in the number of muscle synergies and high similarity among the weight vectors (correlation values range from 0.75 to 0.97). Moreover, differences in terms of average recruitment levels and balance control strategies were detected, suggesting a slightly different modular organization between "well-balanced" and "unbalanced" single-leg stance. In conclusion, this approach can be successfully used as a pre-processing step before muscle synergy extraction, allowing for a better assessment of motor control strategies during the single-leg stance task

Limb reconstruction with knee mega-prosthesis in patients with distal femur primary tumours: gait analysis and alignment evaluation

Introduction: The aim of this study was the functional evaluation and lower limb alignment assessment of patients with a modular knee prosthesis after distal femur resection for primary bone tumour. Materials and methods: 15 patients affected by distal femur tumor and treated with a megaprosthesis implant (6 females and 9 males, mean age: 41 years, range: 15-74 years) and 15 controls were recruited for the study. For each subject the function evaluation included an instrumented gait analysis, while only patients underwent a teleradiography and a latero-lateral X-ray projection of the knee. Results: The duration of the stance phase of gait was shortened in the prosthetic limb with respect to the contralateral limb (57.5±3.6 % gait cycle vs. 60.9±4.8 % gait cycle, P = 0.01), with a correspondent increase of the swing phase. The prosthetic limb also showed an altered knee joint kinematic curve during gait, with a flexion deficit at load response with respect to the contralateral limb (4.5±3.6° vs. 13.4±5.0°, P = 0.000003). Abnormal timing in the muscle activation intervals were observed for tibialis anterior, gastrocnemius lateralis and rectus femoris of the prosthetic limb. The prosthetic limb was found to be misaligned with respect to the contralateral limb, both for the femorotibial (P<0.05) and the ankle joints (P<0.05). Conclusions: Gait analysis performed widely in reference centres could lead to a change in the design of megaprostheses to improve the function and prevent degenerative changes in not involved joint. A multicentric expertise is mandator