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Fasano A.,University of Western Ontario | Herman T.,Center for the Study of Movement | Tessitore A.,The Second University of Naples | Strafella A.P.,University of Western Ontario | Bohnen N.I.,University of Michigan
Journal of Parkinson's Disease | Year: 2015

Functional brain imaging techniques appear ideally suited to explore the pathophysiology of freezing of gait (FOG). In the last two decades, techniques based on magnetic resonance or nuclear medicine imaging have found a number of structural changes and functional disconnections between subcortical and cortical regions of the locomotor network in patients with FOG. FOG seems to be related in part to disruptions in the "executive-attention" network along with regional tissue loss including the premotor area, inferior frontal gyrus, precentral gyrus, the parietal and occipital areas involved in visuospatial functions of the right hemisphere. Several subcortical structures have been also involved in the etiology of FOG, principally the caudate nucleus and the locomotor centers in the brainstem. Maladaptive neural compensation may present transiently in the presence of acute conflicting motor, cognitive or emotional stimulus processing, thus causing acute network overload and resulting in episodic impairment of stepping. In this review we will summarize the state of the art of neuroimaging research for FOG. We will also discuss the limitations of current approaches and delineate the next steps of neuroimaging research to unravel the pathophysiology of this mysterious motor phenomenon. © 2015-IOS Press and the authors. Source


Trojaniello D.,University of Sassari | Ravaschio A.,University of Genoa | Hausdorff J.M.,Center for the Study of Movement | Hausdorff J.M.,Tel Aviv University | Cereatti A.,University of Sassari
Gait and Posture | Year: 2015

The estimation of gait temporal parameters with inertial measurement units (IMU) is a research topic of interest in clinical gait analysis. Several methods, based on the use of a single IMU mounted at waist level, have been proposed for the estimate of these parameters showing satisfactory performance when applied to the gait of healthy subjects. However, the above mentioned methods were developed and validated on healthy subjects and their applicability in pathological gait conditions was not systematically explored. We tested the three best performing methods found in a previous comparative study on data acquired from 10 older adults, 10 hemiparetic, 10 Parkinson's disease and 10 Huntington's disease subjects. An instrumented gait mat was used as gold standard. When pathological populations were analyzed, missed or extra events were found for all methods and a global decrease of their performance was observed to different extents depending on the specific group analyzed. The results revealed that none of the tested methods outperformed the others in terms of accuracy of the gait parameters determination for all the populations except the Parkinson's disease subjects group for which one of the methods performed better than others. The hemiparetic subjects group was the most critical group to analyze (stride duration errors between 4-5 % and step duration errors between 8-13 % of the actual values across methods). Only one method provides estimates of the stance and swing durations which however should be interpreted with caution in pathological populations (stance duration errors between 6-14 %, swing duration errors between 10-32 % of the actual values across populations). © 2015 Elsevier B.V. Source


Ihlen E.A.F.,Norwegian University of Science and Technology | Weiss A.,Center for the Study of Movement | Bourke A.,Norwegian University of Science and Technology | Helbostad J.L.,Norwegian University of Science and Technology | And 2 more authors.
Journal of Biomechanics | Year: 2016

Complexity of human physiology and physical behavior has been suggested to decrease with aging and disease and make older adults more susceptible to falls. The present study investigates complexity in daily life walking in community-dwelling older adult fallers and non-fallers measured by a 3D inertial accelerometer sensor fixed to the lower back. Complexity was expressed using new metrics of entropy: refined composite multiscale entropy (RCME) and refined multiscale permutation entropy (RMPE). The study re-analyses data of 3 days daily-life activity originally described by Weiss et al. (2013). The data set contains inertial sensor data from 39 older persons reporting less than 2 falls and 32 older persons reporting two or more falls during the previous year. The RCME and the RMPE were derived for trunk acceleration and velocity signals from walking epochs of 50. s using mean and variance coarse graining of the signals. Discriminant abilities of the entropy metrics were assessed using a partial least square discriminant analysis. Both RCME and RMPE successfully distinguished between the daily-life walking of the fallers and non-fallers (AUC>0.8) and performed better than the 35 conventional gait features investigated by Weiss et al. (2013). Higher complexity was found in the vertical and mediolateral directions in the non-fallers for both entropy metrics. These findings suggest that RCME and RMPE can be used to improve the assessment of fall risk in older people. © 2016 Elsevier Ltd. Source


Ihlen E.A.F.,Norwegian University of Science and Technology | Weiss A.,Center for the Study of Movement | Beck Y.,Center for the Study of Movement | Helbostad J.L.,Norwegian University of Science and Technology | And 2 more authors.
Journal of Biomechanics | Year: 2016

In the present study we compared the performance of three different estimations of local dynamic stability λ to distinguish between the dynamics of the daily-life walking of elderly fallers and non-fallers. The study re-analyses inertial sensor data of 3-days daily-life activity originally described by Weiss et al. (2013). The data set contains inertial sensor data from 39 older persons who reported less than 2 falls and 31 older persons who reported two or more falls the previous year. 3D-acceleration and 3D-velocity signals from walking epochs of 50. s were used to reconstruct a state space using three different methods. Local dynamic stability was estimated with the algorithms proposed by Rosenstein et al. (1993), Kantz (1994), and Ihlen et al. (2012a). Median λs assessed by Ihlen's and Kantz' algorithms discriminated better between elderly fallers and non-fallers (highest AUC=0.75 and 0.73) than Rosenstein's algorithm (highest AUC=0.59). The present results suggest that the ability of λ to distinguish between fallers and non-fallers is dependent on the parameter setting of the chosen algorithm. Further replication in larger samples of community-dwelling older persons and different patient groups is necessary before including the suggested parameter settings in fall risk assessment and prediction models. © 2016 Elsevier Ltd. Source


Trojaniello D.,University of Sassari | Cereatti A.,University of Sassari | Pelosin E.,University of Genoa | Avanzino L.,University of Genoa | And 4 more authors.
Journal of NeuroEngineering and Rehabilitation | Year: 2014

Background: The step-by-step determination of the spatio-temporal parameters of gait is clinically relevant since it provides an estimation of the variability of specific gait patterns associated with frequent geriatric syndromes. In recent years, several methods, based on the use of magneto-inertial units (MIMUs), have been developed for the step-by-step estimation of the gait temporal parameters. However, most of them were applied to the gait of healthy subjects and/or of a single pathologic population. Moreover, spatial parameters in pathologic populations have been rarely estimated step-by-step using MIMUs. The validity of clinically suitable MIMU-based methods for the estimation of spatio-temporal parameters is therefore still an open issue. The aim of this study was to propose and validate a method for the determination of both temporal and spatial parameters that could be applied to normal and heavily compromised gait patterns. Methods: Two MIMUs were attached above each subject's ankles. An instrumented gait mat was used as gold standard. Gait data were acquired from ten hemiparetic subjects, ten choreic subjects, ten subjects with Parkinson's disease and ten healthy older adults walking at two different gait speeds. The method detects gait events (GEs) taking advantage of the cyclic nature of gait and exploiting some lower limb invariant kinematic characteristics. A combination of a MIMU axes realignment along the direction of progression and of an optimally filtered direct and reverse integration is used to determine the stride length. Results: Over the 4,514 gait cycles analyzed, neither missed nor extra GEs were generated. The errors in identifying both initial and final contact at comfortable speed ranged between 0 and 11 ms for the different groups analyzed. The stride length was estimated for all subjects with less than 3% error. Conclusions: The proposed method is apparently extremely robust since gait speed did not substantially affect its performance and both missed and extra GEs were avoided. The spatio-temporal parameters estimates showed smaller errors than those reported in previous studies and a similar level of precision and accuracy for both healthy and pathologic gait patterns. The combination of robustness, precision and accuracy suggests that the proposed method is suitable for routine clinical use. © 2014 Trojaniello et al. Source

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