Turning Characteristics of the More-Affected Side in Parkinson's Disease Patients with Freezing of Gait

Gait asymmetry and symptom laterality in Parkinson's disease: two of a kind?

BACKGROUND

The laterality of motor symptoms is considered a key feature of Parkinson's disease (PD). Here, we investigated whether gait and turning asymmetry coincided with symptom laterality as determined by the MDS-UPRDS part III and whether it was increased compared to healthy controls (HC).

METHODS

We analyzed the asymmetry of gait and turning with and without a cognitive dual task (DT) using motion capture systems and wearable sensors in 97 PD patients mostly from Hoehn & Yahr stage II and III and 36 age-matched HC. We also assessed motor symptom asymmetry using the bilateral sub-items of the MDS-UPDRS-III. Finally, we examined the strength of the association between gait asymmetry and symptom laterality.

RESULTS

Participants with PD had increased gait but not more turning asymmetry compared to HC (p < 0.05). Only 53.7% of patients had a shorter step length on the more affected body side as determined by the MDS-UPDRS-III. Also, 54% took more time and 29% more steps during turns toward the more affected side. The degree of asymmetry in the different domains did not correlate with each other and was not influenced by DT-load.

CONCLUSIONS

We found a striking mismatch between the side and the degree of asymmetry in different motor domains, i.e., in gait, turning, and distal symptom severity in individuals with PD. We speculate that motor execution in different body parts relies on different neural control mechanisms. Our findings warrant further investigation to understand the complexity of gait asymmetry in PD.

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

Motor cortex hemodynamic response to goal-oriented and non-goal-oriented tasks in healthy subjects

Background

Motor disorders are one of the world's major scourges, and neuromotor rehabilitation is paramount for prevention and monitoring plans. In this scenario, exercises and motor tasks to be performed by patients are crucial to follow and assess treatments' progression and efficacy. Nowadays, in clinical environments, quantitative assessment of motor cortex activities during task execution is rare, due to the bulkiness of instrumentation and the need for immobility during measurements [e.g., functional magnetic resonance imaging (MRI)]. Functional near-infrared spectroscopy (fNIRS) can contribute to a better understanding of how neuromotor processes work by measuring motor cortex activity non-invasively in freely moving subjects.

Aim

Exploit fNIRS to measure functional activation of the motor cortex area during arm-raising actions.

Design

All subjects performed three different upper limbs motor tasks: arm raising (non-goal-oriented), arm raising and grasping (goal oriented), and assisted arm raising (passive task). Each task was repeated ten times. The block design for each task was divided into 5 seconds of baseline, 5 seconds of activity, and 15 seconds of recovery.

Population

Sixteen healthy subjects (11 males and 5 females) with an average (+/- standard deviation) of 37.9 (+/- 13.0) years old.

Methods

Cerebral hemodynamic responses have been recorded in two locations, motor cortex (activation area) and prefrontal cortex (control location) exploiting commercial time-domain fNIRS devices. Haemodynamic signals were analyzed, separating the brain cortex hemodynamic response from extracerebral hemodynamic variations.

Results

The hemodynamic response was recorded in the cortical motor area for goal-oriented and not-goaloriented tasks, while no response was noticed in the control location (prefrontal cortex position).

Conclusions

This study provides a basis for canonical upper limb motor cortex activations that can be potentially compared to pathological cerebral responses in patients. It also highlights the potential use of TD-fNIRS to study goal-oriented versus non-goaloriented motor tasks. Impact: the findings of this study may have implications for clinical rehabilitation by providing a better understanding of the neural mechanisms underlying goal-oriented versus non-goal-oriented motor tasks. This may lead to more effective rehabilitation strategies for individuals with motor disorders and a more effective diagnosis of motor dysfunction supported by objective and quantitative neurophysiological readings.

Association between Severity of Freezing of Gait and Turning Characteristics in People with Parkinson's Disease

For people with Parkinson's disease (PD) with freezing of gait (FOG) (freezers), symptoms mainly exhibit as unilateral motor impairments that may cause difficulty during postural transitions such as turning during daily activities. We investigated the turning characteristics that distinguished freezers among people with PD and analyzed the association between the New Freezing of Gait Questionnaire (NFOGQ) scores and the gait characteristics according to the turning direction for the affected limbs of freezers. The study recruited 57 people with PD (27 freezers, 30 non-freezers). All experiments measured the maximum 180° turning task with the "Off" medication state. Results revealed that the outer ankle range of motion in the direction of the inner step of the more affected limb (IMA) was identified to distinguish freezers and non-freezers (R_N² = 0.735). In addition, higher NFOGQ scores were associated with a more significant anteroposterior root mean square distance of the center of mass in the IMA direction and a greater inner stance phase in the outer step of the more affected limb (OMA) direction; explanatory power was 50.1%. Assessing the maximum speed and turning direction is useful for evaluating the differences in turning characteristics between freezers and non-freezers, which can help define freezers more accurately.

Classification of Parkinson's disease with freezing of gait based on 360° turning analysis using 36 kinematic features

BACKGROUND

Freezing of gait (FOG) is a sensitive problem, which is caused by motor control deficits and requires greater attention during postural transitions such as turning in people with Parkinson's disease (PD). However, the turning characteristics have not yet been extensively investigated to distinguish between people with PD with and without FOG (freezers and non-freezers) based on full-body kinematic analysis during the turning task. The objectives of this study were to identify the machine learning model that best classifies people with PD and freezers and reveal the associations between clinical characteristics and turning features based on feature selection through stepwise regression.

METHODS

The study recruited 77 people with PD (31 freezers and 46 non-freezers) and 34 age-matched older adults. The 360° turning task was performed at the preferred speed for the inner step of the more affected limb. All experiments on the people with PD were performed in the "Off" state of medication. The full-body kinematic features during the turning task were extracted using the three-dimensional motion capture system. These features were selected via stepwise regression.

RESULTS

In feature selection through stepwise regression, five and six features were identified to distinguish between people with PD and controls and between freezers and non-freezers (PD and FOG classification problem), respectively. The machine learning model accuracies revealed that the random forest (RF) model had 98.1% accuracy when using all turning features and 98.0% accuracy when using the five features selected for PD classification. In addition, RF and logistic regression showed accuracies of 79.4% when using all turning features and 72.9% when using the six selected features for FOG classification.

CONCLUSION

We suggest that our study leads to understanding of the turning characteristics of people with PD and freezers during the 360° turning task for the inner step of the more affected limb and may help improve the objective classification and clinical assessment by disease progression using turning features.