Freezing of Gait

Some wearable solutions exploiting on-body acceleration sensors have been proposed to recognize Freezing of Gait (FoG) in people affected by Parkinson Disease (PD). Once a FoG event is detected, these systems generate a sequence of rhythmic stimuli to allow the patient restarting the march. While these solutions are effective in detecting FoG events, they are unable to predict FoG to prevent its occurrence. This paper fills in the gap by presenting a machine learning-based approach that classifies accelerometer data from PD patients, recognizing a pre-FOG phase to further anticipate FoG occurrence in advance. Gait was monitored by three tri-axial accelerometer sensors worn on the back, hip and ankle. Gait features were then extracted from the accelerometer's raw data through data windowing and non-linear dimensionality reduction. A k-nearest neighbor algorithm (k-NN) was used to classify gait in three classes of events: pre-FoG, no-FoG and FoG. The accuracy of the proposed solution was compared to stateof-the-art approaches. Our study showed that: (i) we achieved performances overcoming the state-of-the-art approaches in terms of FoG detection, (ii) we were able, for the very first time in the literature, to predict FoG by identifying the pre-FoG events with an average sensitivity and specificity of, respectively, 94.1% and 97.1%, and (iii) our algorithm can be executed on resource-constrained devices. Future applications include the implementation on a mobile device, and the administration of rhythmic stimuli by a wearable device to help the patient overcome the FoG.

La enfermedad de Parkinson (EP) es un trastorno progresivo neurodegenerativo, cuyo impacto principal radica en la pérdida de la habilidad motora incluyendo temblores, rigidez, desequilibrio y congelamiento de la marcha (FOG de sus siglas en inglés). Los eventos de FOG se inician de manera repentina y consisten en una detención parcial o total de la marcha durante periodos cortos de tiempo, presentándose cuando el paciente atraviesa lugares estrechos o sobre obstáculos, afectando su forma de caminar y provocando incluso caídas y fracturas. En este documento se presenta el diseño, implementación y evaluación de un dispositivo electrónico de estimulación periférica que a través de estímulos vibratorios durante la marcha ayuda a este tipo de pacientes a reducir significativamente los episodios de FOG y mejorar su cadencia. Adicionalmente, el sistema registra parámetros como aceleración en los ejes horizontal y vertical, así como distribución de presión en cuatro puntos específicos de la planta de los pies para un análisis a posteriori de la fisiología de la marcha.

Background: Although a growing number of studies focus on the measurement and detection of freezing of gait (FoG) in laboratory settings, only a few studies have attempted to measure FoG during daily life with body-worn sensors. Here, we presented a novel algorithm to detect FoG in a group of people with Parkinson's disease (PD) in the laboratory (Study I) and extended the algorithm in a second cohort of people with PD at home during daily life (Study II). In Study I, we described of our novel FoG detection algorithm based on five inertial sensors attached to the feet, shins and lumbar region while walking in 40 participants with PD. We compared the performance of the algorithm with two expert clinical raters who scored the number of FoG episodes from video recordings of walking and turning based on duration of the episodes: very short (< 1 s), short (2-5 s), and long (> 5 s). In Study II, a different cohort of 48 people with PD (with and without FoG) wore 3 wearable sensors on their feet and lumbar region for 7 days. Our primary outcome measures for freezing were the % time spent freezing and its variability. We showed moderate to good agreement in the number of FoG episodes detected in the laboratory (Study I) between clinical raters and the algorithm (if wearable sensors were placed on the feet) for short and long FoG episodes, but not for very short FoG episodes. When extending this methodology to unsupervised home monitoring (Study II), we found that percent time spent freezing and the variability of time spent freezing differentiated between people with and without FoG (p < 0.05), and that short FoG episodes account for 69% of the total FoG episodes. Our findings showed that objective measures of freezing in PD using inertial sensors on the feet in the laboratory are matching well with clinical scores. Although results found during daily life are promising, they need to be validated. Objective measures of FoG with wearable technology during community-living would be useful for managing this distressing feature of mobility disability in PD.

Freezing of Gait (FoG) is one of the most debilitating symptoms of Parkinson’s disease and is an important contributor to falls. When the management of freezing episodes cannot be achieved through medication or surgery, non-pharmacological methods, such as cueing, have emerged as effective techniques, which ameliorates FoG. The use of On-Demand cueing systems (systems that only provide cueing stimuli during a FoG episode) has received attention in recent years. For such systems, the most common method of triggering the onset of cueing stimuli, utilize autonomous real-time FoG detection algorithms. In this article, we assessed the potential of a simple double-tap gesture interaction to trigger the onset of cueing stimuli. The intended purpose of our study was to validate the use of double-tap gesture interaction to facilitate Self-activated On-Demand cueing. We present analyses that assess if PwP can perform a double-tap gesture, if the gesture can be detected using an accelerometer’...

Freezing of gait is one of the most debilitating symptoms of Parkinson’s disease and is an important contributor to falls, leading to it being a major cause of hospitalization and nursing home admissions. When the management of freezing episodes cannot be achieved through medication or surgery, non-pharmacological methods such as cueing have received attention in recent years. Novel cueing systems were developed over the last decade and have been evaluated predominantly in laboratory settings. However, to provide benefit to people with Parkinson’s and improve their quality of life, these systems must have the potential to be used at home as a self-administer intervention. This paper aims to provide a technological review of the literature related to wearable cueing systems and it focuses on current auditory, visual and somatosensory cueing systems, which may provide a suitable intervention for use in home-based environments. The paper describes the technical operation and effectiven...

Background: The pathophysiology of freezing of gait (FOG) in non-demented Parkinson's disease (PD) patients remains poorly understood. Recent studies have suggested that neurochemical alterations in the cholinergic systems play a role in the development of FOG. Here, we evaluated the association between subcortical cholinergic structures and FOG in patients with non-demented PD. Methods: We recruited 46 non-demented patients with PD, categorized into PD with (n ¼ 16) and without FOG (n ¼ 30) groups. We performed neuropsychological test, region-of-interest-based volumetric analysis of the substantia innominata (SI) and automatic analysis of subcortical brain structures using a computerized segmentation procedure. Results: The comprehensive neuropsychological assessment showed that PD patients with FOG had lower cognitive performance in the frontal executive and visual-related functions compared with those without freezing of gait. The normalized SI volume did not differ significantly between the two groups (1.65 AE 0.18 vs. 1.68 AE 0.31). The automatic analysis of subcortical structures revealed that the thalamic volumes were significantly reduced in PD patients with FOG compared with those without FOG after adjusting for age, sex, disease duration, the Unified PD Rating Scale scores and total intracranial volume (left: 6.71 vs. 7.16 cm 3 , p ¼ 0.029, right: 6.47 vs. 6.91 cm 3 , p ¼ 0.026). Multiple linear regression analysis revealed that thalamic volume showed significant positive correlations with visual recognition memory (left: b ¼ 0.441, p ¼ 0.037, right: b ¼ 0.498, p ¼ 0.04). Conclusions: These data suggest that thalamic volume and related visual recognition, rather than the cortical cholinergic system arising from the SI, may be a major contributor to the development of freezing of gait in non-demented patients with PD.

Background-Freezing of gait is a disabling symptom of Parkinson's disease (PD) that involves failure to initiate and continue motor activity appropriately. PD disrupts fronto-basal ganglia circuitries that also implement the inhibition of responses, leading to the hypothesis that freezing of gait may involve fundamental changes in both initiation and inhibition of motor actions. Objective-We asked whether PD patients who show freezing of gait show selective deficits in their ability to inhibit upper and lower extremity reactions. Method-We compared older healthy controls, older PD controls without freezing of gait, and older PD participants with freezing of gait, in stop-signal tasks that measured the initiation (go trials) and inhibition (stop trials) of both hand and foot responses.

This study aims at investigating whether impaired anticipatory postural adjustments (APA) during gait initiation contribute to the occurrence of freezing of gait (FOG) or whether altered APAs compensate for FOG in Parkinson's disease (PD). Methods: Gait initiation after 30 s quiet stance was analyzed without and with a cognitive dual task (DT) in 33 PD subjects with FOG (PD+FOG), 30 PD subjects without FOG (PD-FOG), and 32 healthy controls (HC). APAs were characterized with inertial sensors and muscle activity of the tensor fasciae latae (TFL), gastrocnemius, and tibialis anterior was captured with electromyography recordings. Nine trials (of 190) were associated with start hesitation/FOG and analyzed separately. Results: PD+FOG and PD-FOG did not differ in disease duration, disease severity, age, or gender. PD+FOG had significantly smaller medio-lateral (ML) and anterioposterior APAs compared to PD-FOG (DT, p < 0.05). PD+FOG had more cocontraction of left and right TFL during APAs compared to PD-FOG (p < 0.01). Within the PD+FOG, the ML size of APA (DT) was positively correlated with the severity of FOG history (NFOG-Q), with larger APAs associated with worse FOG (rho = 0.477, p = 0.025). ML APAs were larger during trials with observed FOG compared to trials of PD+FOG without FOG. Conclusions: People with PD who have a history of FOG have smaller ML APAs (weight shifting) during gait initiation compared to PD-FOG and HC. However, start hesitation (FOG) is not caused by an inability to sufficiently displace the center of mass toward the stance leg because APAs were larger during trials with observed FOG. We speculate that reducing the acceleration of the body center of mass with hip abductor co-contraction for APAs might be a compensatory strategy in PD+FOG, to address postural control deficits and enable step initiation.

Freezing of gait (FoG) is typically a symptom of advanced Parkinson&#39;s disease (PD) that negatively influences the quality of life and is often resistant to pharmacological interventions. Novel treatment options that make use of auditory or sensory cues might be optimized by prediction of freezing events. These predictions might help to trigger external sensory cues—shown to improve walking performance—when behavior is changed in a manner indicative of an impending freeze (i.e., when the user needs it the most), rather than delivering cue information continuously. A data-driven approach is proposed for predicting freezing events using Random Forrest (RF), Neural Network (NN), and Naive Bayes (NB) classifiers. Vertical forces, sampled at 100 Hz from a force platform were collected from 9 PD subjects as they stepped in place until they at least had one freezing episode or for 90 s. The F1 scores of RF/NN/NB algorithms were computed for different IL (input to the machine learning al...

Freezing of Gait (FoG) is one of the most debilitating symptom of patients with Parkinson Disease (PwP) as it could leads to fall and loss of independence. It is common in Parkinson&#39;s disease but, interestingly, it doesn&#39;t occur in all patients [1], suggesting that PwP with FoG are a subpopulation of PwP [2]. Known triggers for FoG include, aside to normal gait, challenging events that require precise regulation of complex motor sequences to control step length and gait timing, such as step initiation and raise to walk. Motor and cognitive models have been proposed to explain the potential mechanisms behind the episodic nature of FoG [3]. FoG is typically considered a motor deficit. However, recent researches suggest that declining cognitive/executive functions, in set-shifting and inhibition, may also contribute to FoG [4, 5]. Somewhat related, individuals with Parkinson&#39;s disease who exhibit FoG have difficulty shifting their attention when performing online modificati...

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

Falls and gait impairment in Parkinson&#39;s Disease (PD) is a leading cause of morbidity and mortality, significantly impacting quality of life and contributing heavily to disability. Thus far axial symptoms, such as postural instability and gait freezing, have been refractory to current treatment approaches and remain a critical unmet need. There has been increased excitement surrounding the surgical targeting of the pedunculopontine nucleus (PPN) for addressing axial symptoms in PD. The PPN and cuneate nucleus comprise the mesencephalic locomotor region, and electrophysiologic studies in animal models and human imaging studies have revealed a key role for the PPN in gait and postural control, underscoring a potential role for DBS surgery. Previous limited studies of PPN deep brain stimulation (DBS) in treating gait symptoms have had mixed clinical outcomes, likely reflect targeting variability and the inherent challenges of targeting a small brainstem structure that is both anato...

Freezing of gait (FOG) is one of the most incapacitating symptoms among the motor alterations of Parkinson's disease (PD). Manifesting FOG episodes reduce patients' quality of life and their autonomy to perform daily living activities, while it may provoke falls. Accurate ambulatory FOG assessment would enable non-pharmacologic support based on cues and would provide relevant information to neurologists on the disease evolution. This paper presents a method for FOG detection based on deep learning and signal processing techniques. This is, to the best of our knowledge, the first time that FOG detection is addressed with deep learning. The evaluation of the model has been done based on the data from 15 PD patients who manifested FOG. An inertial measurement unit placed at the left side of the waist recorded tri-axial accelerometer, gyroscope and magnetometer signals. Our approach achieved comparable results to the state-of-the-art, reaching validation performances of 88.6% and 78% for sensitivity and specificity respectively.

Human gait activity recognition is an emerging field of motion analysis that can be applied in various application domains. One of the most attractive applications includes monitoring of gait disorder patients, tracking their disease progression and the modification/evaluation of drugs. This paper proposes a robust, wearable gait motion data acquisition system that allows either the classification of recorded gait data into desirable activities or the identification of common risk factors, thus enhancing the subject’s quality of life. Gait motion information was acquired using accelerometers and gyroscopes mounted on the lower limbs, where the sensors were exposed to inertial forces during gait. Additionally, leg muscle activity was measured using strain gauge sensors. As a matter of fact, we wanted to identify different gait activities within each gait recording by utilizing Machine Learning algorithms. In line with this, various Machine Learning methods were tested and compared to...

BackgroundGait disturbances are critical motor symptoms in Parkinson’s disease (PD). The mechanisms of gait impairment in PD are not entirely understood but likely involve changes in the Pedunculopontine Nucleus (PPN), a critical locomotion center, and its associated connections. Exercise is universally accepted as helpful in PD, but the extent and intensity of exercise required for plastic changes are unclear.MethodsTwenty-seven PD subjects participated in a 3-month gait training intervention. Clinical assessments and resting-state functional magnetic resonance imaging were performed at baseline and 3 months after exercise. Functional connectivity of PPN was assessed by combining the methods of partial least squares, conditional dependence and partial correlation. In addition, paired t-tests were used to examine the effect of exercise on PPN functional connectivity and clinical measures, and Pearson’s correlation was used to assess the association between altered PPN functional con...

ObjectiveTo estimate the effect of a physiotherapist-delivered fall prevention programme for people with Parkinson’s (PwP).MethodsPeople at risk of falls with confirmed Parkinson’s were recruited to this multicentre, pragmatic, investigator blind, individually randomised controlled trial with prespecified subgroup analyses. 474 PwP (Hoehn and Yahr 1–4) were randomised: 238 allocated to a physiotherapy programme and 236 to control. All participants had routine care; the control group received a DVD about Parkinson’s and single advice session at trial completion. The intervention group (PDSAFE) had an individually tailored, progressive home-based fall avoidance strategy training programme with balance and strengthening exercises. The primary outcome was risk of repeat falling, collected by self-report monthly diaries, 0–6 months after randomisation. Secondary outcomes included Mini-BESTest for balance, chair stand test, falls efficacy, freezing of gait, health-related quality of life ...

La enfermedad de Parkinson (EP) es un trastorno progresivo neurodegenerativo, cuyo impacto principal radica en la pérdida de la habilidad motora incluyendo temblores, rigidez, desequilibrio y congelamiento de la marcha (FOG de sus siglas en inglés). Los eventos de FOG se inician de manera repentina y consisten en una detención parcial o total de la marcha durante periodos cortos de tiempo, presentándose cuando el paciente atraviesa lugares estrechos o sobre obstáculos, afectando su forma de caminar y provocando incluso caídas y fracturas. En este documento se presenta el diseño, implementación y evaluación de un dispositivo electrónico de estimulación periférica que a través de estímulos vibratorios durante la marcha ayuda a este tipo de pacientes a reducir significativamente los episodios de FOG y mejorar su cadencia. Adicionalmente, el sistema registra parámetros como aceleración en los ejes horizontal y vertical, así como distribución de presión en cuatro puntos específicos de la planta de los pies para un análisis a posteriori de la fisiología de la marcha.

Currently, the “best practice” employed for rehabilitation is based on attentional strategies, and on the use of temporal or spatial external stimuli (cues) to facilitate the initiation and ongoing motor activity. However, these strategies may generate an important dependence that implies to rely critically on cues in the environment. Moreover, in certain circumstances, cueing may trigger freezing episodes as dual task conditions. Re-Learning motor strategies without cues (i.e. using action observation [1]) can be an alternative/innovative approach to rehabilitation that relies more on appropriate allocation of attention and lightening cognitive load.

Freezing of gait (FoG) is one of the most disabling gait disorders in Parkinson's disease (PD), reflecting motor and cognitive impairments, mainly related to dopamine deficiency. Recent studies investigating kinematic and kinetic factors affecting gait in these patients showed a postural instability characterized by disturbed weight-shifting, inappropriate anticipatory postural adjustment, worse reactive postural control, and a difficulty executing complex motor tasks (i.e. sit-to-walk). These symptoms are difficult to alleviate and not very responsive to Levodopa. For this reason, additional therapeutic actions based on specific therapeutic protocols may help patients with their daily lives. We conducted a randomized control trial aimed to test if two clinical protocols for PD patients with FoG were effective to improve postural control. Methods: Rehabilitation protocols, conceived to improve gait, were based on learning motor exercises with the Action Observation plus Sonification (AOS) technique, or by the use of external sensory cues. We collected biomechanical data (Center of Mass COM, Center of Pressure COP, and moving timings), using the sit-to-walk task as a measure of motor and gait performance. Results: Kinetic and kinematic data showed that when treatment effects consolidate, patients treated with AOS protocol are more efficient in merging subsequent motor tasks (sit-to-stand and gait initiation), and diminished the total moving time and the area of the COP positions. Conclusion: We demonstrated for the first time that PD patients with FoG treated with an AOS protocol aimed at relearning appropriate gait patterns increased balance control and re-acquired more efficient postural control.

Freezing of gait (FoG) is a disabling symptom associated with falls, with little or no responsiveness to pharmacological treatment. Current protocols used for rehabilitation are based on the use of external sensory cues. However, cued strategies might generate an important dependence on the environment. Teaching motor strategies without cues [i.e., action observation (AO) plus Sonification] could represent an alternative/innovative approach to rehabilitation that matters most on appropriate allocation of attention and lightening cognitive load. We aimed to test the effects of a novel experimental protocol to treat patients with Parkinson&#39;s disease (PD) and FoG, using functional, and clinical scales. The experimental protocol was based on AO plus Sonification. 12 patients were treated with 8 motor gestures. They watched eight videos showing an actor performing the same eight gestures, and then tried to repeat each gesture. Each video was composed by images and sounds of the gestu...

Recent studies suggest that depression and anxiety in patients with Parkinson's disease may predispose them to freezing. Although festination is also frequent, the association with emotional disorders has not been examined. The aim of the authors was to clarify the association between freezing and festination with anxiety, depressive disorders, and emotional distress. The authors examined a consecutive series of 95 patients with Parkinson's disease using comprehensive psychiatric assessments and a new instrument specifically designed to assess the severity of freezing, festination, and emotional distress (Motor Blocks and Festination Scale). All patients were assessed with the Motor Blocks and Festination Scale, the Mini International Neuropsychiatric Interview, and scales to measure the severity of mood and anxiety disorders. A linear regression analysis showed that both motor blocks and festination were significantly associated with emotional distress and deficits on activities of daily living. Conversely, there was no significant association between motor blocks or festination and generalized anxiety disorder, panic disorder, agoraphobia, social phobia, or depression. Motor blocks and festination are significantly associated with emotional distress, but no significant associations were found with anxiety or affective disorders.

Background: Movement disorders are neurologic syndromes that produce abnormal movements, being Parkinson's disease (PD) the most frequent. Current diagnosis of Parkinson's disease is clinical: it is based on expertise, which can result in diagnostic errors and treatment deficits. Quantitative diagnosis is reached searching objective parameters, a quantity that correlates with the phenomenon we want to quantify. Quantitative measures of movement are a novel approach to assist physicians in the diagnosis of Parkinson's disease. Objective: To find a quantitative feature in accelerometery signals that distinguishes parkinsonian patients from age-matched control subjects. Method: We designed and developed an ergonomic wristband with proper electronics attached, including inertial sensors and control logic to manage the data signals. Additionally, we developed a mobile app for logging and administration of data signals. We measured limb acceleration in two groups of people: a group of patients with Parkinson's disease (n = 11) and an age-matched control group (n = 10). Acceleration signals were measured during the evaluation of finger tapping (from the motor subscore of the Unified Parkinson's Disease Rating Scale-UPDRS part III). To characterize the signals, we developed mathematical tools based on the analysis of temporal and frequency patterns. Power spectrum analysis of the signals exhibited a power law relationship between variables with different frequency ranges. Results: Interpreting the finger tapping task as an input to the motor system, variations in the scale invariance bandwidth can be related to the mechanic system's control response. Analyzing the power spectrum of the patient group signals, a statistical relevant reduction (p<0.005) is found in the frequency range that follows a power law (Linear Invariance Range, LIR) compared to the control group. LIR quantity calculated correlates with the gold standard clinical diagnosis MDS-UPDRS-III. Conclusion: The LIR quantity allows proposing a reduction of the scale. The quantity LIR found is proposed as a possible signal related biomarker of Parkinson's disease.

Specific impairments of anticipatory postural adjustment (APA) during step initiation have been reported in patients with Parkinson's disease (PD) and freezing of gait (FoG). Although APA disruption has been associated with FoG, there is scarce knowledge about its neural correlates. We sought to better understand the neural networks involved with APA in patients with FoG by assessing the level of hemodynamic response of specific brain regions and the functional connectivity during the leg lifting task. In the current investigation, APAs of patients with PD, with and without (nFoG) freezing were assessed during a leg lifting task in an event-related, functional magnetic resonance imaging (er-fMRI) protocol. Results identified a high hemodynamic response in the right anterior insula (AI) and supplementary motor area (SMA) in the FoG group when an APA was required. The nFoG had stronger connectivity between the right and left insulae than the FoG group. The strength of this connectivity was negatively correlated with the severity of FoG. Both groups showed different brain network organizations comprising the SMA and the bilateral AI. The SMA was found to be a hub in patients with FoG when an APA was required for the task. Our findings suggest that both groups used compensatory mechanism comprising the insulae during APA. Neither group used the entire network comprised of the insulae and SMA to accomplish the task. The FoG group relied more on SMA as a hub than as part of a broader network to exchange information during the APA.

Specific impairments of anticipatory postural adjustment (APA) during step initiation have been reported in patients with Parkinson's disease (PD) and freezing of gait (FoG). Although APA disruption has been associated with FoG, there is scarce knowledge about its neural correlates. We sought to better understand the neural networks involved with APA in patients with FoG by assessing the level of hemodynamic response of specific brain regions and the functional connectivity during the leg lifting task. In the current investigation, APAs of patients with PD, with and without (nFoG) freezing were assessed during a leg lifting task in an event-related, functional magnetic resonance imaging (er-fMRI) protocol. Results identified a high hemodynamic response in the right anterior insula (AI) and supplementary motor area (SMA) in the FoG group when an APA was required. The nFoG had stronger connectivity between the right and left insulae than the FoG group. The strength of this connectivity was negatively correlated with the severity of FoG. Both groups showed different brain network organizations comprising the SMA and the bilateral AI. The SMA was found to be a hub in patients with FoG when an APA was required for the task. Our findings suggest that both groups used compensatory mechanism comprising the insulae during APA. Neither group used the entire network comprised of the insulae and SMA to accomplish the task. The FoG group relied more on SMA as a hub than as part of a broader network to exchange information during the APA.

Freezing of gait is a devastating symptom of advanced Parkinson's disease yet the neural correlates of this phenomenon remain poorly understood. In this study, severity of freezing of gait was assessed in 18 patients with Parkinson's disease on a series of timed 'up and go' tasks, in which all patients suffered from episodes of clinical freezing of gait. The same patients also underwent functional magnetic resonance imaging with a virtual reality gait paradigm, performance on which has recently been shown to correlate with actual episodes of freezing of gait. Statistical parametric maps were created that compared the blood oxygen leveldependent response associated with paroxysmal motor arrests (freezing) to periods of normal motor output. The results of a random effects analysis revealed that these events were associated with a decreased blood oxygen level-dependent response in sensorimotor regions and an increased response within frontoparietal cortical regions. These signal changes were inversely correlated with the severity of clinical freezing of gait. Motor arrests were also associated with decreased blood oxygen level-dependent signal bilaterally in the head of caudate nucleus, the thalamus and the globus pallidus internus. Utilizing a mixed event-related/block design, we found that the decreased blood oxygen level-dependent response in the globus pallidus and the subthalamic nucleus persisted even after controlling for the effects of cognitive load, a finding which supports the notion that paroxysmal increases in basal ganglia outflow are associated with the freezing phenomenon. This method also revealed a decrease in the blood oxygen level-dependent response within the mesencephalic locomotor region during motor arrests, the magnitude of which was positively correlated with the severity of clinical freezing of gait. These results provide novel insights into the pathophysiology underlying freezing of gait and lend support to models of freezing of gait that implicate dysfunction across coordinated neural networks.

Freezing of gait (FOG) in Parkinson's disease (PD) is frequently triggered upon passing through narrow spaces such as doorways. However, despite being common the neural mechanisms underlying this phenomenon are poorly understood. In our study, 19 patients who routinely experience FOG performed a previously validated virtual reality (VR) gait paradigm where they used foot-pedals to navigate a series of doorways. Patients underwent testing randomised between both their "ON" and "OFF" medication states. Task performance in conjunction with blood oxygenation level dependent (BOLD) signal changes between "ON" and "OFF" states were compared within each patient. Specifically, as they passed through a doorway in the VR environment patients demonstrated significantly longer "footstep" latencies in the OFF state compared to the ON state. As seen clinically in FOG this locomotive delay was primarily triggered by narrow doorways rather than wide doorways. Functional magnetic resonance imaging revealed that footstep prolongation on passing through doorways was associated with selective hypoactivation in the presupplementary motor area (pSMA) bilaterally. Task-based functional connectivity analyses revealed that increased latency in response to doorways was inversely correlated with the degree of functional connectivity between the pSMA and the subthalamic nucleus (STN) across both hemispheres. Furthermore, increased frequency of prolonged footstep latency was associated with increased connectivity between the bilateral STN. These findings suggest that the effect of environmental cues on triggering FOG reflects a degree of impaired processing within the pSMA and disrupted signalling between the pSMA and STN, thus implicating the "hyperdirect" pathway in the generation of this phenomenon.

Recent neuroimaging evidence has led to the proposal that freezing of gait in Parkinson's disease is due to dysfunctional interactions between frontoparietal cortical regions and subcortical structures, such as the striatum. However, to date, no study has employed task-based functional connectivity analyses to explore this hypothesis. In this study, we used a data-driven multivariate approach to explore the impaired communication between distributed neuronal networks in 10 patients with Parkinson's disease and freezing of gait, and 10 matched patients with no clinical history of freezing behaviour. Patients performed a virtual reality gait task on two separate occasions (once ON and once OFF their regular dopaminergic medication) while functional magnetic resonance imaging data were collected. Group-level independent component analysis was used to extract the subject-specific time courses associated with five well-known neuronal networks: the motor network, the right-and left cognitive control networks, the ventral attention network and the basal ganglia network. We subsequently analysed both the activation and connectivity of these neuronal networks between the two groups with respect to dopaminergic state and cognitive load while performing the virtual reality gait task. During task performance, all patients used the left cognitive control network and the ventral attention network and in addition, showed increased connectivity between the bilateral cognitive control networks. However, patients with freezing demonstrated functional decoupling between the basal ganglia network and the cognitive control network in each hemisphere. This decoupling was also associated with paroxysmal motor arrests. These results support the hypothesis that freezing behaviour in Parkinson's disease is because of impaired communication between complimentary yet competing neural networks.

Gait disturbances, including freezing of gait, are frequent and disabling symptoms of Parkinson&#39;s disease. They often respond poorly to dopaminergic treatments. Although recent studies have shed some light on their neural correlates, their modulation by dopaminergic treatment remains quite unknown. Specifically, the influence of levodopa on the networks involved in motor imagery (MI) of parkinsonian gait has not been directly studied, comparing the off and on medication states in the same patients. We therefore conducted an [H2150] Positron emission tomography study in eight advanced parkinsonian patients (mean disease duration: 12.3 ± 3.8 years) presenting with levodopa‐responsive gait disorders and FoG, and eight age‐matched healthy subjects. All participants performed three tasks (MI of gait, visual imagery and a control task). Patients were tested off, after an overnight withdrawal of all antiparkinsonian treatment, and on medication, during consecutive mornings. The order o...

Objectives: This study examined if people with Parkinson's and freezing of gait pathology (FoG) could be trained to increase preparatory weight-shift amplitude, and facilitate step initiation during FoG. Methods: Thirty-five people with Parkinson's and FoG attempted to initiate forward walking from a stationary position caused by a freeze (n = 17, FoG-F) or voluntarily stop (n = 18, FoG-NF) in a Baseline condition and two conditions where an increased weight-shift amplitude was trained via: (i) explicit verbal instruction, and (ii) implicit movement analogies. Results: At Baseline, weight-shift amplitudes were smaller during: (i) unsuccessful, compared to successful step initiations (FoG-F group), and (ii) successful step initiations in the FoG-F group compared to FoG-NF. Both Verbal and Analogy training resulted in significant increases in weight-shift amplitude in both groups, and a corresponding pronounced reduction in unsuccessful attempts to initiate stepping (FoG-F group). Conclusions: Hypometric preparatory weight-shifting is associated with failure to initiate forward stepping in people with Parkinson's and FoG. However, impaired weight-shift characteristics are modifiable through conscious strategies. This current study provides a novel and critical evaluation of preparatory weight-shift amplitudes during FoG events. The intervention described represents an attractive 'rescue' strategy and should be further scrutinised regarding limitations posed by physical and cognitive deficits.

Background: Freezing of gait is a common (FOG) episodic gait disorder in advanced Parkinson's disease (PD). FOG is one of the main risk factors for falls; therefore FOG's consequences can be devastating. This symptom is difficult to study in a research laboratory because of its unpredictability which makes it difficult to select patients for clinical testing and make the right treatment decisions. Thus, clinical indicators may be useful to distinguish between patients with and without FOG. The aim of this study was to compare the number of steps and the time to perform a 180-degree turn in patients with Parkinson's disease with and without FOG. Material and methods: The study was performed on 56 PD patients. Subjects were divided into 2 groups: a total of 28 patients with PD and FOG were compared with 28 patients with PD without FOG, according to item number 14, from the Unified Parkinson's Disease Rating Scale (UPDRS). The 2 subgroups were homogeneous in terms of age and disease severity. Results: Significant differences were found between the two groups both in steps number (P <0.0001) and in the time required to perform a 180-degree turn (P <0.0001). Conclusions: Performing more steps and more seconds to turn 180 degrees may be a useful indicator to distinguish the characteristics of PD patients with FOG. A PD patient which turns at 180-degree with more than 5 steps is most likely a patient with FOG.

Yor J. Castaño Grupo de Investigación i2t Universidad Icesi. Cali, Colombia [email protected] Andrés Navarro Grupo de Investigación i2t Universidad Icesi. Cali, Colombia [email protected] Juan D. Arango Grupo de Investigación i2t Universidad Icesi. Bogota, Colombia [email protected] Beatriz E. Muñoz Cĺınica Fundación Valle del Lili. Cali, Colombia [email protected] Jorge L. Orozco Cĺınica Fundación Valle del Lili. Cali, Colombia [email protected] Jaime Valderrama Cĺınica Fundación Valle del Lili. Cali, Colombia [email protected]

Parkinson’s disease (PD) is a neurodegenerative disease that mainly affects people older than 60 years and is characterized by a neuronal loss in several brain areas, but particularly in the substantia nigra, which can lead initially to motor alterations like gait asymmetry and delayed to cognitive disorders. To detect the alterations, two bracelets with integrated electronic devices capable of sensing upper limbs motion in Parkinson’s patients has been developed to analyze and calculate gait asymmetry indicator that allows the detection of PD in early stages. The device will measure movement variables in the patient’s arms through accelerometers and the information produced by the bracelets is sent to a smartphone via Bluetooth 4.0 protocol and then stored in the cloud. The stored data analysis is useful to medical specialists in order to detect motor alterations and make decisions.

Parkinson's disease (PD) is responsible for a broad spectrum of signs and symptoms, including relevant motor impairments generally rated by clinical experts. In recent years, motor measurements gathered by technology-based systems have been used more and more to provide objective data. In particular, wearable devices have been adopted to evidence differences in the gait capabilities between PD patients and healthy people. Within this frame, despite the key role that the upper limbs' swing plays during walking, no studies have been focused on their harmonic content, to which this work is devoted. To this end, we measured, by means of IMU sensors, the walking capabilities of groups of PD patients (both de novo and under-chronic-dopaminergic-treatment patients when in an off-therapy state) and their healthy counterparts. The collected data were FFT transformed, and the frequency content was analyzed. According to the results obtained, PD determines upper limb rigidity objectively evidenced and correlated to lower harmonic contents.

Background: The simultaneous completion of multiple tasks (dual-tasking, DT) often leads to poorer task performance (DT cost, DTC). People with Parkinson’s disease (PwPD) exhibit difficulty with DT, and DTC may be particularly pronounced in PwPD with freezing of gait (FOG). Objective: This study assessed the relationship between FOG status and DTC during gait. Methods: Gait parameters were collected using inertial sensors in 106 PwPD (off-medication), including definite-freezers (dFOG; n = 25), possible-freezers (pFOG; n = 16), and non-freezers (nFOG; n = 65) during single (ST)-and DT walking. Results: PwPD with dFOG had larger (worse) DTC than nFOG for foot-strike angle, stride length, toe-off angle, variability of foot-strike angle, and arm range of motion (ROM). After accounting for covariates, the toe-off angle and stride length remained worse in PwPD who freeze. Worse cognition predicted larger DTC for stride length, gait cycle duration, gait speed, and step duration across gro...

Background: Movement disorders are neurologic syndromes that produce abnormal movements, being Parkinson's disease (PD) the most frequent. Current diagnosis of Parkinson's disease is clinical: it is based on expertise, which can result in diagnostic errors and treatment deficits. Quantitative diagnosis is reached searching objective parameters, a quantity that correlates with the phenomenon we want to quantify. Quantitative measures of movement are a novel approach to assist physicians in the diagnosis of Parkinson's disease. Objective: To find a quantitative feature in accelerometery signals that distinguishes parkinsonian patients from age-matched control subjects. Method: We designed and developed an ergonomic wristband with proper electronics attached, including inertial sensors and control logic to manage the data signals. Additionally, we developed a mobile app for logging and administration of data signals. We measured limb acceleration in two groups of people: a group of patients with Parkinson's disease (n = 11) and an age-matched control group (n = 10). Acceleration signals were measured during the evaluation of finger tapping (from the motor subscore of the Unified Parkinson's Disease Rating Scale-UPDRS part III). To characterize the signals, we developed mathematical tools based on the analysis of temporal and frequency patterns. Power spectrum analysis of the signals exhibited a power law relationship between variables with different frequency ranges. Results: Interpreting the finger tapping task as an input to the motor system, variations in the scale invariance bandwidth can be related to the mechanic system's control response. Analyzing the power spectrum of the patient group signals, a statistical relevant reduction (p<0.005) is found in the frequency range that follows a power law (Linear Invariance Range, LIR) compared to the control group. LIR quantity calculated correlates with the gold standard clinical diagnosis MDS-UPDRS-III. Conclusion: The LIR quantity allows proposing a reduction of the scale. The quantity LIR found is proposed as a possible signal related biomarker of Parkinson's disease.

Freezing of gait (FOG) is one of the most incapacitating symptoms among the motor alterations of Parkinson's disease (PD). Manifesting FOG episodes reduce patients' quality of life and their autonomy to perform daily living activities, while it may provoke falls. Accurate ambulatory FOG assessment would enable non-pharmacologic support based on cues and would provide relevant information to neurologists on the disease evolution. This paper presents a method for FOG detection based on deep learning and signal processing techniques. This is, to the best of our knowledge, the first time that FOG detection is addressed with deep learning. The evaluation of the model has been done based on the data from 15 PD patients who manifested FOG. An inertial measurement unit placed at the left side of the waist recorded tri-axial accelerometer, gyroscope and magnetometer signals. Our approach achieved comparable results to the state-of-the-art, reaching validation performances of 88.6% and 78% for sensitivity and specificity respectively.

Yor J. Castaño Grupo de Investigación i2t Universidad Icesi. Cali, Colombia [email protected] Andrés Navarro Grupo de Investigación i2t Universidad Icesi. Cali, Colombia [email protected] Juan D. Arango Grupo de Investigación i2t Universidad Icesi. Bogota, Colombia [email protected] Beatriz E. Muñoz Cĺınica Fundación Valle del Lili. Cali, Colombia [email protected] Jorge L. Orozco Cĺınica Fundación Valle del Lili. Cali, Colombia [email protected] Jaime Valderrama Cĺınica Fundación Valle del Lili. Cali, Colombia [email protected]

Gait disturbances, including freezing of gait, are frequent and disabling symptoms of Parkinson's disease. They often respond poorly to dopaminergic treatments. Although recent studies have shed some light on their neural correlates, their modulation by dopaminergic treatment remains quite unknown. Specifically, the influence of levodopa on the networks involved in motor imagery (MI) of parkinsonian gait has not been directly studied, comparing the off and on medication states in the same patients. We therefore conducted an [H 2 15 0] Positron emission tomography study in eight advanced parkinsonian patients (mean disease duration: 12.3 6 3.8 years) presenting with levodoparesponsive gait disorders and FoG, and eight age-matched healthy subjects. All participants performed three tasks (MI of gait, visual imagery and a control task). Patients were tested off, after an overnight withdrawal of all antiparkinsonian treatment, and on medication, during consecutive mornings. The order of conditions was counterbalanced between subjects and sessions. Results showed that imagined gait elicited activations within motor and frontal associative areas, thalamus, basal ganglia and

Freezing of gait (FOG) is one of the most incapacitating symptoms among the motor alterations of Parkinson's disease (PD). Manifesting FOG episodes reduce patients' quality of life and their autonomy to perform daily living activities, while it may provoke falls. Accurate ambulatory FOG assessment would enable non-pharmacologic support based on cues and would provide relevant information to neurologists on the disease evolution. This paper presents a method for FOG detection based on deep learning and signal processing techniques. This is, to the best of our knowledge, the first time that FOG detection is addressed with deep learning. The evaluation of the model has been done based on the data from 15 PD patients who manifested FOG. An inertial measurement unit placed at the left side of the waist recorded tri-axial accelerometer, gyroscope and magnetometer signals. Our approach achieved comparable results to the state-of-the-art, reaching validation performances of 88.6% and 78% for sensitivity and specificity respectively.