Refinement of an Algorithm to Detect and Predict Freezing of Gait in Parkinson Disease Using Wearable Sensors.

Freezing of gait (FOG) is a debilitating symptom of Parkinson disease (PD). It is episodic and variable in nature, making assessment difficult. Wearable sensors used in conjunction with specialized algorithms, such as our group's pFOG algorithm, provide objective data to better understand this phenomenon.

Differential components of bradykinesia in Parkinson's disease revealed by deep brain stimulation.

Bradykinesia is a term describing several manifestations of movement disruption caused by Parkinson's disease (PD), including movement slowing, amplitude reduction, and gradual decrease of speed and amplitude over multiple repetitions of the same movement. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves bradykinesia in patients with PD. We examined the effect of DBS on specific components of bradykinesia when applied at two locations within the STN, using signal processing techniques to identify the time course of amplitude and frequency of repeated hand pronation-supination movements performed by participants with and without PD.

Corticospinal and corticoreticulospinal projections benefit motor behaviors in chronic stroke.

Unlabelled: After corticospinal tract (CST) stroke, several motor deficits in the upper extremity (UE) emerge, including diminished muscle strength, motor control, and muscle individuation. Both the ipsilesional CST and contralesional corticoreticulospinal tract (CReST) innervate the paretic UE and may have different innervation patterns for the proximal and distal UE segments. These patterns may underpin distinct pathway relationships to separable motor behaviors.

Using Wearable Sensors to Assess Freezing of Gait in the Real World.

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) that remains difficult to assess. Wearable movement sensors and associated algorithms can be used to quantify FOG in laboratory settings, but the utility of such methods for real world use is unclear. We aimed to determine the suitability of our wearable sensor-based FOG assessment method for real world use by assessing its performance during in-clinic simulated real world activities.

Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities.

Instrumented footwear represents a promising technology for spatiotemporal gait analysis in out-of-the-lab conditions. However, moderate accuracy impacts this technology's ability to capture subtle, but clinically meaningful, changes in gait patterns that may indicate adverse outcomes or underlying neurological conditions. This limitation hampers the use of instrumented footwear to aid functional assessments and clinical decision making.

A walking dance to improve gait speed for people with Parkinson disease: a pilot study.

To determine the effectiveness of a targeted dance intervention to improve walking speed for people with Parkinson disease (PD) by increasing motor motivation.  11 participants with PD participated in a 6-week pilot study in which they learned a contemporary dance composed of walking steps and designed to mimic everyday walking. 1 h classes occurred twice-weekly.

Design of the WHIP-PD study: a phase II, twelve-month, dual-site, randomized controlled trial evaluating the effects of a cognitive-behavioral approach for promoting enhanced walking activity using mobile health technology in people with Parkinson-disease.

Background: Parkinson disease (PD) is a debilitating and chronic neurodegenerative disease resulting in ambulation difficulties. Natural walking activity often declines early in disease progression despite the relative stability of motor impairments. In this study, we propose a paradigm shift with a "connected behavioral approach" that targets real-world walking using cognitive-behavioral training and mobile health (mHealth) technology.

Gait Cycle Validation and Segmentation Using Inertial Sensors.

In this paper, we develop an algorithm to automatically validate and segment a gait cycle in real time into three gait events, namely midstance, toe-off, and heel-strike, using inertial sensors. We first use the physical models of sensor data obtained from a foot-mounted inertial system to differentiate stationary and moving segments of the sensor data. Next, we develop an optimization routine called sparsity-assisted wavelet denoising (SAWD), which simultaneously combines linear time invariant filters, orthogonal multiresolution representations such as wavelets, and sparsity-based methods, to generate a sparse template of the moving segments of the gyroscope measurements in the sagittal plane for valid gait cycles.

Predicting Cognitive Improvement in Normal Pressure Hydrocephalus Patients Using Preoperative Neuropsychological Testing and Cerebrospinal Fluid Biomarkers.

Background: Though it is well known that normal pressure hydrocephalus (NPH) patients can cognitively improve after ventriculoperitoneal shunting (VPS), one of the major dilemmas in NPH is the ability to prospectively predict which patients will improve.

Objective: To prospectively assess preoperative predictors of postshunt cognitive improvement.

Methods: This was a prospective observational cohort including 52 consecutive patients with approximately 1-yr follow-up.

A Single, Continuously Applied Control Policy for Modeling Reaching Movements with and without Perturbation.

It has been debated whether kinematic features, such as the number of peaks or decomposed submovements in a velocity profile, indicate the number of discrete motor impulses or result from a continuous control process. The debate is particularly relevant for tasks involving target perturbation, which can alter movement kinematics. To simulate such tasks, finite-horizon models require two preset movement durations to compute two control policies before and after the perturbation.

DYT1 dystonia increases risk taking in humans.

It has been difficult to link synaptic modification to overt behavioral changes. Rodent models of DYT1 dystonia, a motor disorder caused by a single gene mutation, demonstrate increased long-term potentiation and decreased long-term depression in corticostriatal synapses. Computationally, such asymmetric learning predicts risk taking in probabilistic tasks.

Motor fluctuations due to interaction between dietary protein and levodopa in Parkinson's disease.

Background: The modulation of levodopa transport across the blood brain barrier by large neutral amino acids is well documented. Protein limitation and protein redistribution diets may improve motor fluctuations in patients with Parkinson's disease but the pharmacokinetics and pharmacodynamics of levodopa and amino acids are highly variable.

Methods: Clinical records of 1037 Parkinson's disease patients were analyzed to determine the proportion of patients with motor fluctuations related to protein interaction with levodopa.

variants and glucocerebrosidase activity in Parkinson's disease.

Mutations in glucocerebrosidase () are a common risk factor for Parkinson's disease (PD). The scavenger receptor class B member 2 () gene encodes a receptor responsible for the transport of glucocerebrosidase (GCase) to the lysosome. Two common SNPs in linkage disequilibrium with , rs6812193 and rs6825004, have been associated with PD and Lewy Body Disease in genome wide association studies.

Robotic therapy for chronic stroke: general recovery of impairment or improved task-specific skill?

There is a great need to develop new approaches for rehabilitation of the upper limb after stroke. Robotic therapy is a promising form of neurorehabilitation that can be delivered in higher doses than conventional therapy. Here we sought to determine whether the reported effects of robotic therapy, which have been based on clinical measures of impairment and function, are accompanied by improved motor control.

Glucocerebrosidase activity in Parkinson's disease with and without GBA mutations.

Glucocerebrosidase (GBA) mutations have been associated with Parkinson's disease in numerous studies. However, it is unknown whether the increased risk of Parkinson's disease in GBA carriers is due to a loss of glucocerebrosidase enzymatic activity. We measured glucocerebrosidase enzymatic activity in dried blood spots in patients with Parkinson's disease (n = 517) and controls (n = 252) with and without GBA mutations.

Persistent residual errors in motor adaptation tasks: reversion to baseline and exploratory escape.

When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback.

The neural correlates of learned motor acuity.

We recently defined a component of motor skill learning as "motor acuity," quantified as a shift in the speed-accuracy trade-off function for a task. These shifts are primarily driven by reductions in movement variability. To determine the neural correlates of improvement in motor acuity, we devised a motor task compatible with magnetic resonance brain imaging that required subjects to make finely controlled wrist movements under visual guidance.

Learning fast accurate movements requires intact frontostriatal circuits.

The basal ganglia are known to play a crucial role in movement execution, but their importance for motor skill learning remains unclear. Obstacles to our understanding include the lack of a universally accepted definition of motor skill learning (definition confound), and difficulties in distinguishing learning deficits from execution impairments (performance confound). We studied how healthy subjects and subjects with a basal ganglia disorder learn fast accurate reaching movements.

Parkinson disease phenotype in Ashkenazi Jews with and without LRRK2 G2019S mutations.

The phenotype of Parkinson's disease (PD) in patients with and without leucine-rich repeat kinase 2 (LRRK2) G2019S mutations reportedly is similar; however, large, uniformly evaluated series are lacking. The objective of this study was to characterize the clinical phenotype of Ashkenazi Jewish (AJ) PD carriers of the LRRK2 G2019S mutation. We studied 553 AJ PD patients, including 65 patients who were previously reported, from three sites (two in New York and one in Tel-Aviv).

Clinical characteristics of patients with spinocerebellar ataxias 1, 2, 3 and 6 in the US; a prospective observational study.

Background: All spinocerebellar ataxias (SCAs) are rare diseases. SCA1, 2, 3 and 6 are the four most common SCAs, all caused by expanded polyglutamine-coding CAG repeats. Their pathomechanisms are becoming increasingly clear and well-designed clinical trials will be needed.

Unlearning versus savings in visuomotor adaptation: comparing effects of washout, passage of time, and removal of errors on motor memory.

Humans are able to rapidly adapt their movements when a visuomotor or other systematic perturbation is imposed. However, the adaptation is forgotten or unlearned equally rapidly once the perturbation is removed. The ultimate cause of this unlearning remains poorly understood.

The role of neuroplasticity in dopaminergic therapy for Parkinson disease.

Dopamine replacement is a mainstay of therapeutic strategies for Parkinson disease (PD). The motor response to therapy involves an immediate improvement in motor function, known as the short-duration response (SDR), followed by a long-duration response (LDR) that develops more slowly, over weeks. Here, we review evidence in patients and animal models suggesting that dopamine-dependent corticostriatal plasticity, and retention of such plasticity in the absence of dopamine, are the mechanisms underlying the LDR.

Movement duration, Fitts's law, and an infinite-horizon optimal feedback control model for biological motor systems.

Optimization models explain many aspects of biological goal-directed movements. However, most such models use a finite-horizon formulation, which requires a prefixed movement duration to define a cost function and solve the optimization problem. To predict movement duration, these models have to be run multiple times with different prefixed durations until an appropriate duration is found by trial and error.