Freezing Of Gait Episodes Research Articles

Prediction of Freezing of Gait in Parkinson's Disease Using Statistical Inference and Lower-Limb Acceleration Data.

The freezing of gait (FoG) is a common type of motor dysfunction in advanced Parkinson's disease (PD) associated with falls. Over the last decade, a significant amount of studies has been focused on detecting FoG episodes in clinical and home environments. Yet, there remains a paucity of techniques regarding real-time prediction of FoG before its occurrence. In this paper, a new algorithm was employed to define the best combination of sensor position, axis, sampling window length, and features to predict FoG. We hypothesized that gait deterioration before FoG onsets can be discriminated from normal gait using statistical analysis of features from successive windows of data collected from lower-limb accelerometers. We defined a new performance measure, "predictivity", to compare the number of correctly predicted FoG events among different combinations. We characterized the system performance using data from 10 PD patients, who experienced FoG while performing several walking tasks in a lab environment. The analysis of 120 different combinations revealed that prediction of FoG can be realized by using an individual shank sensor and sample entropy calculated from the horizontal forward axis with window length of 2 s (88.8%, 92.5%, and 89.0% for average predictivity, sensitivity, and specificity, respectively).

Wearable Sensors System for an Improved Analysis of Freezing of Gait in Parkinson's Disease Using Electromyography and Inertial Signals.

We propose a wearable sensor system for automatic, continuous and ubiquitous analysis of Freezing of Gait (FOG), in patients affected by Parkinson’s disease. FOG is an unpredictable gait disorder with different clinical manifestations, as the trembling and the shuffling-like phenotypes, whose underlying pathophysiology is not fully understood yet. Typical trembling-like subtype features are lack of postural adaptation and abrupt trunk inclination, which in general can increase the fall probability. The targets of this work are detecting the FOG episodes, distinguishing the phenotype and analyzing the muscle activity during and outside FOG, toward a deeper insight in the disorder pathophysiology and the assessment of the fall risk associated to the FOG subtype. To this aim, gyroscopes and surface electromyography integrated in wearable devices sense simultaneously movements and action potentials of antagonist leg muscles. Dedicated algorithms allow the timely detection of the FOG episode and, for the first time, the automatic distinction of the FOG phenotypes, which can enable associating a fall risk to the subtype. Thanks to the possibility of detecting muscles contractions and stretching exactly during FOG, a deeper insight into the pathophysiological underpinnings of the different phenotypes can be achieved, which is an innovative approach with respect to the state of art.

A Non-Invasive Medical Device for Parkinson’s Patients with Episodes of Freezing of Gait

A critical symptom of Parkinson’s disease (PD) is the occurrence of Freezing of Gait (FOG), an episodic disorder that causes frequent falls and consequential injuries in PD patients. There are various auditory, visual, tactile, and other types of stimulation interventions that can be used to induce PD patients to escape FOG episodes. In this article, we describe a low cost wearable system for non-invasive gait monitoring and external delivery of superficial vibratory stimulation to the lower extremities triggered by FOG episodes. The intended purpose is to reduce the duration of the FOG episode, thus allowing prompt resumption of gait to prevent major injuries. The system, based on an Android mobile application, uses a tri-axial accelerometer device for gait data acquisition. Gathered data is processed via a discrete wavelet transform-based algorithm that precisely detects FOG episodes in real time. Detection activates external vibratory stimulation of the legs to reduce FOG time. The integration of detection and stimulation in one low cost device is the chief novel contribution of this work. We present analyses of sensitivity, specificity and effectiveness of the proposed system to validate its usefulness.

Crossing Virtual Doors: A New Method to Study Gait Impairments and Freezing of Gait in Parkinson's Disease.

Studying freezing of gait (FOG) in the lab has proven problematic. This has primarily been due to the difficulty in designing experimental setups that maintain high levels of ecological validity whilst also permitting sufficient levels of experimental control. To help overcome these challenges, we have developed a virtual reality (VR) environment with virtual doorways, a situation known to illicit FOG in real life. To examine the validity of this VR environment, an experiment was conducted, and the results were compared to a previous “real-world” experiment. A group of healthy controls (N = 10) and a group of idiopathic Parkinson disease (PD) patients without any FOG episodes (N = 6) and with a history of freezing (PD-f, N = 4) walked under three different virtual conditions (no door, narrow doorway (100% of shoulder width) and standard doorway (125% of shoulder width)). The results were similar to those obtained in the real-world setting. Virtual doorways reduced step length and velocity while increasing general gait variability. The PD-f group always walked slower, with a smaller step length, and showed the largest increases in gait variability. The narrow doorway induced FOG in 66% of the trials, while the standard doorway caused FOG in 29% of the trials. Our results closely mirrored those obtained with real doors. In short, this methodology provides a safe, personalized yet adequately controlled means to examine FOG in Parkinson's patients, along with possible interventions.

Sensory Electrical Stimulation Cueing May Reduce Freezing of Gait Episodes in Parkinson's Disease.

Introduction Freezing of gait (FoG) is a movement abnormality that presents with advancing Parkinson's disease (PD) and is one of the most debilitating symptoms of the disease. The mainstay of nonpharmacological management of FoG is typically through external cueing techniques designed to relieve or prevent the freezing episode. Previous work shows that electrical stimulation may prove useful as a gait guidance technique, but further evidence is required. The main objective of this study was to determine whether a “fixed” rhythmic sensory electrical stimulation (sES) cueing strategy would significantly (i) reduce the time taken to complete a walking task and (ii) reduce the number of FoG episodes occurring when performing the task. Methods 9 participants with idiopathic PD performed a self-identified walking task during both control (no cue) and cueing conditions. The self-identified walking task was a home-based daily walking activity, which was known to result in FoG for that person. A trained physiotherapist recorded the time taken to complete the walking task and the number of FoG episodes which occurred during the task. Data were analyzed by paired t-tests for both the time to complete a walking task and the number of FoG episodes occurring. Results sES cueing resulted in a reduction in the time taken to complete a walking task and in the number of FoG episodes occurring during performance of this task by 14.23 ± 11.15% (p=0.009) and 58.28 ± 33.89% (p=0.002), respectively. Conclusions This study shows a positive effect of “fixed” rhythmic sES on the time taken to complete a walking task and on the number of FoG episodes occurring during the task. Our results provide evidence that sES cueing delivered in a “fixed” rhythmic manner has the potential to be an effective cueing mechanism for FoG prevention.

T50. Freezing of gait does not modulate neural oscillations in motor cortices

Introduction Walking abilities are severely affected in patients with freezing of gait (FOG), a common phenomenon in advanced stages of Parkinson’s disease (PD). Despite the high occurrence of FOG, little is known about the underlying mechanisms. Interestingly, it was reported that patients with FOG are still able to ride a bike (Snijders AH et al., Bicycling breaks the ice for freezers of gait, Mov Disord 2011). While similar brain networks are involved in walking and bicycling (Fukuyama H et al., Brain functional activity during gait in normal subjects: A SPECT study, Neurosci Lett 1997; Christensen LOD et al., Cerebral activation during bicycle movements in man, Exp Brain Res 2000), it is not completely understood why both types of movement are differently affected in PD patients with FOG. A recent study from our group demonstrated that the oscillatory activity within the subthalamic nucleus (STN) differs between patients with and without FOG (Storzer L et al., Bicycling suppresses abnormal beta synchrony in the Parkinsonian basal ganglia, Ann Neurol 2017). In particular, it was shown that patients with FOG present a characteristic increase of oscillatory activity at ∼18 Hz. The aim of the study was to examine movement-associated cortical oscillatory activity in PD patients with and without FOG. Methods We analyzed EEG data of 19 PD patients with FOG (65.5 ± 7.2 years), 13 PD patients without FOG (61.6 ± 8.1 years), and 16 healthy controls (63.3 ± 7.3 years). Patients were recorded OFF dopaminergic medication using a portable EEG system (Porti, TMSi, Enschede, The Netherlands). Data were recorded during unconstrained walking and bicycling on a stationary bicycle. Measurements consisted of a baseline rest period, continuous movement, and an alternating sequence of rest and movement, i.e. bicycling or walking, for 10 s each. Furthermore, measurements included 180° turns around the body axis during walking condition. Turns were rated for the occurrence of FOG episodes by two different raters. Analyses were focused on oscillatory activity in the beta band and the Cz electrode overlying the leg area of both motor cortices. Statistical testing was performed by fitting linear mixed models using package lme 1.1–13 for R. Results Bicycling and walking were associated with beta power suppression (13–35 Hz). This suppression was stronger for bicycling than for walking ( β = −0.37, p β = −0.11, p = 0.72). Furthermore, within the group of Freezers we did not find cortical differences between turns with FOG and turns without FOG either( β = 0.66, p = 0.4). Conclusion We did not observe cortical beta power changes specifically related to freezing. This finding does not support the notion that the primary motor cortex is crucially involved in generating freezing.

Predictors of freezing of gait in Chinese patients with Parkinson's disease.

ObjectiveTo explore the clinical predictors of freezing of gait (FOG) in Chinese patients with Parkinson's disease (PD).MethodsThis study included 225 patients with PD who completed a three‐year follow‐up visit. The end‐point was the presence of FOG (freezers), which was assessed during the follow‐up visit. Group comparisons were conducted, followed by a further forward binary logistic regression analysis.ResultsEighty‐five patients with PD (38%) had developed FOG at the end of study. At baseline, freezers exhibited higher age, longer disease duration, higher scores in Unified PD Rating Scale (UPDRS) III and Hamilton Depression/Anxiety Rating Scale, lower Frontal Assessment Battery (FAB) score, higher subscores (e.g., “urgency”) and frequencies (e.g., “hallucinations”) in Non‐Motor Symptoms Scale, higher annual changes in MoCA, UPDRS III and FAB scores, and higher incidences of festination and falls than nonfreezers (p < .05). The forward binary logistic regression model indicated that a longer disease duration, a higher UPDRS III score, higher annual changes in UPDRS III score and “visuospatial/executive abilities” subscore, onset in lower limbs, and the presence of festination, falls, and hallucinations were associated with the development of FOG.ConclusionsPatients with onset in the lower limbs and the presence of festination, falls, and hallucinations may be prone to develop FOG episodes. FOG also likely occurs with the deterioration of PD severity and visuospatial function.

The laser shoes: A new ambulatory device to alleviate freezing of gait in Parkinson disease.

To assess, in a cross-sectional study, the feasibility and immediate efficacy of laser shoes, a new ambulatory visual cueing device with practical applicability for use in daily life, on freezing of gait (FOG) and gait measures in Parkinson disease (PD). We tested 21 patients with PD and FOG, both "off" and "on" medication. In a controlled gait laboratory, we measured the number of FOG episodes and the percent time frozen occurring during a standardized walking protocol that included FOG provoking circumstances. Participants performed 10 trials with and 10 trials without cueing. FOG was assessed using offline video analysis by an independent rater. Gait measures were recorded in between FOG episodes with the use of accelerometry. Cueing using laser shoes was associated with a significant reduction in the number of FOG episodes, both "off" (45.9%) and "on" (37.7%) medication. Moreover, laser shoes significantly reduced the percent time frozen by 56.5% (95% confidence interval [CI] 32.5-85.8; p = 0.004) when "off" medication. The reduction while "on" medication was slightly smaller (51.4%, 95% CI -41.8 to 91.5; p = 0.075). These effects were paralleled by patients' positive subjective experience on laser shoes' efficacy. There were no clinically meaningful changes in the gait measures. These findings demonstrate the immediate efficacy of laser shoes in a controlled gait laboratory, and offer a promising intervention with potential to deliver in-home cueing for patients with FOG. This study provides Class III evidence that for patients with PD, laser shoes significantly reduce FOG severity (both number and duration of FOG episodes).

Deep learning for freezing of gait detection in Parkinson’s disease patients in their homes using a waist-worn inertial measurement unit

Among Parkinson’s disease (PD) motor symptoms, freezing of gait (FOG) may be the most incapacitating. FOG episodes may result in falls and reduce patients’ quality of life. Accurate assessment of FOG would provide objective information to neurologists about the patient’s condition and the symptom’s characteristics, while it could enable non-pharmacologic support based on rhythmic cues.This paper is, to the best of our knowledge, the first study to propose a deep learning method for detecting FOG episodes in PD patients. This model is trained using a novel spectral data representation strategy which considers information from both the previous and current signal windows. Our approach was evaluated using data collected by a waist-placed inertial measurement unit from 21 PD patients who manifested FOG episodes. These data were also employed to reproduce the state-of-the-art methodologies, which served to perform a comparative study to our FOG monitoring system.The results of this study demonstrate that our approach successfully outperforms the state-of-the-art methods for automatic FOG detection. Precisely, the deep learning model achieved 90% for the geometric mean between sensitivity and specificity, whereas the state-of-the-art methods were unable to surpass the 83% for the same metric.

L-DOPA and Freezing of Gait in Parkinson's Disease: Objective Assessment through a Wearable Wireless System.

Freezing of gait (FOG) is a leading cause of falls and fractures in Parkinson’s disease (PD). The episodic and rather unpredictable occurrence of FOG, coupled with the variable response to l-DOPA of this gait disorder, makes the objective evaluation of FOG severity a major clinical challenge in the therapeutic management of patients with PD. The aim of this study was to examine and compare gait, clinically and objectively, in patients with PD, with and without FOG, by means of a new wearable system. We also assessed the effect of l-DOPA on FOG severity and specific spatiotemporal gait parameters in patients with and without FOG. To this purpose, we recruited 28 patients with FOG, 16 patients without FOG, and 16 healthy subjects. In all participants, gait was evaluated clinically by video recordings and objectively by means of the wearable wireless system, during a modified 3-m Timed Up and Go (TUG) test. All patients performed the modified TUG test under and not under dopaminergic therapy (ON and OFF therapy). By comparing instrumental data with the clinical identification of FOG based on offline video-recordings, we also assessed the performance of the wearable system to detect FOG automatically in terms of sensitivity, specificity, positive and negative predictive values, and finally accuracy. TUG duration was longer in patients than in controls, and the amount of gait abnormalities was prominent in patients with FOG compared with those without FOG. l-DOPA improved gait significantly in patients with PD and particularly in patients with FOG mainly by reducing FOG duration and increasing specific spatiotemporal gait parameters. Finally, the overall wireless system performance in automatic FOG detection was characterized by excellent sensitivity (93.41%), specificity (98.51%), positive predictive value (89.55%), negative predictive value (97.31%), and finally accuracy (98.51%). Our study overall provides new information on the beneficial effect of l-DOPA on FOG severity and specific spatiotemporal gait parameters as objectively measured by a wearable sensory system. The algorithm here reported potentially opens to objective long-time sensing of FOG episodes in patients with PD.

Identification of Characteristic Motor Patterns Preceding Freezing of Gait in Parkinson's Disease Using Wearable Sensors.

Freezing of gait (FOG) is a disabling symptom that is common among patients with advanced Parkinson’s disease (PD). External cues such as rhythmic auditory stimulation can help PD patients experiencing freezing to resume walking. Wearable systems for automatic freezing detection have been recently developed. However, these systems detect a FOG episode after it has happened. Instead, in this study, a new approach for the prediction of FOG (before it actually happens) is presented. Prediction of FOG might enable preventive cueing, reducing the likelihood that FOG will occur. Moreover, understanding the causes and circumstances of FOG is still an open research problem. Hence, a quantitative characterization of movement patterns just before FOG (the pre-FOG phase) is of great importance. In this study, wearable inertial sensors were used to identify and quantify the characteristics of gait during the pre-FOG phase and compare them with the characteristics of gait that do not precede FOG. The hypothesis of this study is based on the threshold-based model of FOG, which suggests that before FOG occurs, there is a degradation of the gait pattern. Eleven PD subjects were analyzed. Six features extracted from movement signals recorded by inertial sensors showed significant differences between gait and pre-FOG. A classification algorithm was developed in order to test if it is feasible to predict FOG (i.e., detect it before it happens). The aim of the classification procedure was to identify the pre-FOG phase. Results confirm that there is a degradation of gait occurring before freezing. Results also provide preliminary evidence on the feasibility of creating an automatic algorithm to predict FOG. Although some limitations are present, this study shows promising findings for characterizing and identifying pre-FOG patterns, another step toward a better understanding, prediction, and prevention of this disabling symptom.

Usability of Three-dimensional Augmented Visual Cues Delivered by Smart Glasses on (Freezing of) Gait in Parkinson's Disease.

External cueing is a potentially effective strategy to reduce freezing of gait (FOG) in persons with Parkinson’s disease (PD). Case reports suggest that three-dimensional (3D) cues might be more effective in reducing FOG than two-dimensional cues. We investigate the usability of 3D augmented reality visual cues delivered by smart glasses in comparison to conventional 3D transverse bars on the floor and auditory cueing via a metronome in reducing FOG and improving gait parameters. In laboratory experiments, 25 persons with PD and FOG performed walking tasks while wearing custom-made smart glasses under five conditions, at the end-of-dose. For two conditions, augmented visual cues (bars/staircase) were displayed via the smart glasses. The control conditions involved conventional 3D transverse bars on the floor, auditory cueing via a metronome, and no cueing. The number of FOG episodes and percentage of time spent on FOG were rated from video recordings. The stride length and its variability, cycle time and its variability, cadence, and speed were calculated from motion data collected with a motion capture suit equipped with 17 inertial measurement units. A total of 300 FOG episodes occurred in 19 out of 25 participants. There were no statistically significant differences in number of FOG episodes and percentage of time spent on FOG across the five conditions. The conventional bars increased stride length, cycle time, and stride length variability, while decreasing cadence and speed. No effects for the other conditions were found. Participants preferred the metronome most, and the augmented staircase least. They suggested to improve the comfort, esthetics, usability, field of view, and stability of the smart glasses on the head and to reduce their weight and size. In their current form, augmented visual cues delivered by smart glasses are not beneficial for persons with PD and FOG. This could be attributable to distraction, blockage of visual feedback, insufficient familiarization with the smart glasses, or display of the visual cues in the central rather than peripheral visual field. Future smart glasses are required to be more lightweight, comfortable, and user friendly to avoid distraction and blockage of sensory feedback, thus increasing usability.

Influence of Cueing and an Attentional Strategy on Freezing of Gait in Parkinson Disease During Turning.

Individuals with Parkinson disease exhibit decreased axial head-pelvis rotation. Consequently, they turn more en bloc than healthy controls, which may contribute to freezing during turning. We wanted to understand the influence of auditory cueing and an attentional strategy on turning and how this related to freezing of gait (FOG). Fifteen participants with Parkinson disease and FOG were asked to turn 180° during baseline condition, unilateral cueing, and an attentional strategy prompting to start the turn with head rotation first. FOG occurrence, axial rotation, center of mass (COM) deviation, knee-flexion amplitude, and total turn velocity were measured using 3D motion analysis while off-medication. Normal reference values were obtained from 14 age-matched controls. Thirty-nine FOG episodes occurred in 5 participants. FOG occurred in 52.8% of baseline trials compared with 34.6% of trials using the head-first strategy, and 3.8% of the auditory cueing trials. During the head first strategy, the initiation of head, trunk, and pelvic rotation as well as the head-pelvis separation resembled turning patterns of healthy controls, but the COM shift to the inside of the turn was exaggerated. By contrast, during cueing, turning became more en bloc, with decreased head-pelvis separation and knee-flexion amplitude. Cueing reduced FOG but did not correct axial movement deficits. The head-first strategy improved head-pelvis dissociation but had only limited effects on FOG. These results suggest that axial and COM deviation impairments are not directly related to FOG but may rather indicate a compensatory mechanism. Cueing reinforced the en-bloc movement and might as such help prevent FOG by triggering an alternative neural mechanism for movement generation.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A163).

A smartphone-based architecture to detect and quantify freezing of gait in Parkinson’s disease

IntroductionThe freezing of gait (FOG) is a common and highly distressing motor symptom in patients with Parkinson’s Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestation and limited responsiveness to drug treatment. MethodsIn order to verify the acceptance of a smartphone-based architecture and its reliability at detecting FOG in real-time, we studied 20 patients suffering from PD-related FOG. They were asked to perform video-recorded Timed Up and Go (TUG) test with and without dual-tasks while wearing the smartphone. Video and accelerometer recordings were synchronized in order to assess the reliability of the FOG detection system as compared to the judgement of the clinicians assessing the videos. The architecture uses two different algorithms, one applying the Freezing and Energy Index (Moore-Bächlin Algorithm), and the other adding information about step cadence, to algorithm 1. ResultsA total 98 FOG events were recognized by clinicians based on video recordings, while only 7 FOG events were missed by the application. Sensitivity and specificity were 70.1% and 84.1%, respectively, for the Moore-Bächlin Algorithm, rising to 87.57% and 94.97%, respectively, for algorithm 2 (McNemar value=28.42; p=0.0073). ConclusionResults confirm previous data on the reliability of Moore-Bächlin Algorithm, while indicating that the evolution of this architecture can identify FOG episodes with higher sensitivity and specificity. An acceptable, reliable and easy-to-implement FOG detection system can support a better quantification of the phenomenon and hence provide data useful to ascertain the efficacy of therapeutic approaches.

EP 38. Subthalamic nucleus Deep Brain Stimulation (STN-DBS) reduces freezing of gait in Parkinson’s disease in the VANTAGE prospective, multi-center trial

Background Deep Brain Stimulation (DBS) is effective for Parkinson’s disease (PD) symptom relief; however, improvement of freezing of gait (FOG) remains under debate. Some studies indicate STN-DBS alleviates FOG, while others suggest an association of STN-DBS with worsening of gait and balance or even induction of FOG. The VANTAGE study assesses motor improvement in moderate-to-severe PD following bilateral STN-DBS using a new, implantable, rechargeable, multiple-source, 16-output (supporting two 8-contact leads), constant-current, CE-marked DBS System. We report the effects of STN-DBS on FOG in this cohort of PD subjects. Methods VANTAGE is a monitored, prospective, multi-center, non-randomized, open-label interventional trial, sponsored by Boston Scientific Corporation. FOG was characterized with UPDRS-II item 14, the freezing of gait questionnaire (FOGQ) and a walking test known to provoke FOG pre and post-surgery. Data collection included FOGQ at Baseline and 26 weeks post-implantation, and the walking test at Baseline, 12, 26, and 52 weeks post-implantation. The walking test was videotaped and rated remotely by an independent rater (CS), blinded to the subject’s implantation status. Results Thirty-eight subjects, of the forty implanted, were analyzed with FOGQ data. The FOGQ showed significant improvement at 26 week follow up versus baseline derived from UPDRS-III item 29 and UPDRS II item 14. FOGQ (item 3) data at 26 weeks versus baseline indicated 12 freezers remained freezers, 15 freezers turned to non-freezers, 10 non-freezers remained non-freezers, and one non-freezer turned to a freezer. The walking test was performed by 29 of 38 subjects at baseline during medication off. Thirteen subjects showed FOG-episodes off medication at baseline and improved after L-Dopa intake. Postoperatively, the total walking time, FOG episode occurrences, and total time spent frozen were reduced at week 12, 26, and 52 compared to baseline during medication off. Conclusions FOGQ and walking test data demonstrate that STN-DBS can reduce FOG occurrence and severity at 26 weeks postoperatively with constant effects at week 52. Follow-up data will help to understand if improvement on FOG persists long term.

Congelación de la marcha en supra-on: a propósito de dos casos

Over recent years, several types of freezing of gait (FOG) have been described, mainly according to their response to levodopa. FOG in Parkinson's disease presents in a variety of ways due to differences within the underlying pathophysiology. In a number of patients, increasing the dopaminergic stimulation may not improve this condition, and may even worsen it. We present two patients with Parkinson's disease who were evaluated during off, on and supra-on periods. Motor function was assessed with Unified Parkinson's Disease Rating Scale III, tapping test on lower limbs and quantification of FOG episodes during each of these periods. Both patients presented FOG episodes while in off period, experiencing a significant improvement during on period. However, when increasing the dopaminergic stimulation in order to try to improve their motor response, FOG episodes worsened to the point of impairing gait. FOG episodes are not always a consequence of akinesia or rigidity. Regarding the pathophysiology, the lack of an appropriate response to treatment would be explained by the involvement of structures exceeding the substantia nigra and the dopaminergic deficit. FOG worsening during periods of dopaminergic overstimulation could be related to a neurotransmitters disbalance affecting other nuclei involved in postural and gait control.

Detection of freezing of gait for Parkinson’s disease patients with multi-sensor device and Gaussian neural networks

Freezing of Gait (FoG) in Parkinson Disease (PD) is a sudden episode characterized by a brief failure to walk. The aim of this study is to detect FoG episodes using a multi-sensor device for data acquisition, and Gaussian neural networks as a classification tool. Thus we have built a multi sensor prototype that detects FoG using new indicators like the variation of the inter-foot distance or the knee angle. Data are acquired from PD patients having FoG as a major symptom. The major social challenge is obtaining the acknowledgment of patients to participate in our study, whereas the main technical difficulty is extracting efficient features from various walking behaviors. For that purpose, the acquired signals are analyzed in order to extract both time and frequency domain features that separate the FoG class from the other gaits modes. Due to the complexity of FoG episodes, the optimal features are then extracted using Principal Component Analysis technique. Another contribution is to introduce the combined data into the Gaussian Neural Network (GNN) classification method, that is a new technique used for FoG detection, and has been developed in our previous works. Moreover, the classical thresholding method is implemented to compare and validate the GNN method. Results showed the feasibility of integrating the chosen sensors, in addition to the effectiveness of combining data from different types of sensors on the classification rate. The efficiency rate of classification in the proposed method is about 87 %.

Freezing of Gait in Parkinson's Disease: An Overload Problem?

Freezing of gait (FOG) is arguably the most severe symptom associated with Parkinson’s disease (PD), and often occurs while performing dual tasks or approaching narrowed and cluttered spaces. While it is well known that visual cues alleviate FOG, it is not clear if this effect may be the result of cognitive or sensorimotor mechanisms. Nevertheless, the role of vision may be a critical link that might allow us to disentangle this question. Gaze behaviour has yet to be carefully investigated while freezers approach narrow spaces, thus the overall objective of this study was to explore the interaction between cognitive and sensory-perceptual influences on FOG. In experiment #1, if cognitive load is the underlying factor leading to FOG, then one might expect that a dual-task would elicit FOG episodes even in the presence of visual cues, since the load on attention would interfere with utilization of visual cues. Alternatively, if visual cues alleviate gait despite performance of a dual-task, then it may be more probable that sensory mechanisms are at play. In compliment to this, the aim of experiment#2 was to further challenge the sensory systems, by removing vision of the lower-limbs and thereby forcing participants to rely on other forms of sensory feedback rather than vision while walking toward the narrow space. Spatiotemporal aspects of gait, percentage of gaze fixation frequency and duration, as well as skin conductance levels were measured in freezers and non-freezers across both experiments. Results from experiment#1 indicated that although freezers and non-freezers both walked with worse gait while performing the dual-task, in freezers, gait was relieved by visual cues regardless of whether the cognitive demands of the dual-task were present. At baseline and while dual-tasking, freezers demonstrated a gaze behaviour that neglected the doorway and instead focused primarily on the pathway, a strategy that non-freezers adopted only when performing the dual-task. Interestingly, with the combination of visual cues and dual-task, freezers increased the frequency and duration of fixations toward the doorway, compared to non-freezers. These results suggest that although increasing demand on attention does significantly deteriorate gait in freezers, an increase in cognitive demand is not exclusively responsible for freezing (since visual cues were able to overcome any interference elicited by the dual-task). When vision of the lower limbs was removed in experiment#2, only the freezers’ gait was affected. However, when visual cues were present, freezers’ gait improved regardless of the dual-task. This gait behaviour was accompanied by greater amount of time spent looking at the visual cues irrespective of the dual-task. Since removing vision of the lower-limbs hindered gait even under low attentional demand, restricted sensory feedback may be an important factor to the mechanisms underlying FOG.

Center of mass trajectories during turning in patients with Parkinson's disease with and without freezing of gait

BackgroundDespite the strong relationship between freezing of gait (FOG) and turning in Parkinson's disease (PD), few studies have addressed specific postural characteristics during turning that might contribute to freezing. MethodsThirty participants with PD (16 freezers, 14 non-freezers) (all tested OFF medication) and 14 healthy controls walked 5 meters and turned 180° in a 3D gait laboratory. COM behavior was analyzed during four turning quadrants of 40° between 10° and 170° pelvic rotation and during 40° before actual FOG episodes. These pre-FOG segments were compared with similar turning sections in turns of freezers without FOG. Outcome parameters were turn time, COM distance, COM velocity, step width and the medial- and anterior COM position. ResultsTurn time was increased in freezers compared to non-freezers (p=.000). No differences were found regarding COM distance and velocity during turning quadrants between groups and between freezers’ pre-FOG segments and similar turning segments without FOG. Medial COM deviation was reduced in PD patients compared to controls (p=.004), but no differences were found between freezers and non-freezers. In turns with freezing, turn time increased (p=.005) and step width decreased (p=.025) pre-FOG. Freezers also showed a less medial (p=.020) and more anterior (p=.016) COM position pre-FOG compared to turning sections without FOG. ConclusionsOur results revealed no subgroup differences in COM behavior during uninterrupted turning. However, we found a reduced medial deviation, a forward COM shift and a decreased step width in freezers just before FOG episodes. These abnormalities may play a causal role, as they could hamper stability and fluent weight shifting necessary for continued stepping during turning.

Detecting freezing of gait with a tri-axial accelerometer in Parkinson's disease patients.

Freezing of gait (FOG) is a common motor symptom of Parkinson's disease (PD), which presents itself as an inability to initiate or continue gait. This paper presents a method to monitor FOG episodes based only on acceleration measurements obtained from a waist-worn device. Three approximations of this method are tested. Initially, FOG is directly detected by a support vector machine (SVM). Then, classifier's outputs are aggregated over time to determine a confidence value, which is used for the final classification of freezing (i.e., second and third approach). All variations are trained with signals of 15 patients and evaluated with signals from another 5 patients. Using a linear SVM kernel, the third approach provides 98.7% accuracy and a geometric mean of 96.1%. Moreover, it is investigated whether frequency features are enough to reliably detect FOG. Results show that these features allow the method to detect FOG with accuracies above 90% and that frequency features enable a reliable monitoring of FOG by using simply a waist sensor.