Combining olfactory test and motion analysis sensors in Parkinson's disease preclinical diagnosis: a pilot study

Hands-feet wireless devices: Test-retest reliability and discriminant validity of motor measures in Parkinson's disease telemonitoring

BACKGROUND

Telemonitoring, a branch of telemedicine, involves the use of technological tools to remotely detect clinical data and evaluate patients. Telemonitoring of patients with Parkinson's disease (PD) should be performed using reliable and discriminant motor measures. Furthermore, the method of data collection and transmission, and the type of subjects suitable for telemonitoring must be well defined.

OBJECTIVE

To analyze differences in patients with PD and healthy controls (HC) with the wearable inertial device SensHands-SensFeet (SH-SF), adopting a standardized acquisition mode, to verify if motor measures provided by SH-SF have a high discriminating capacity and high intraclass correlation coefficient (ICC).

METHODS

Altogether, 64 patients with mild-to-moderate PD and 50 HC performed 14 standardized motor activities for assessing bradykinesia, postural and resting tremors, and gait parameters. SH-SF inertial devices were used to acquire movements and calculate objective motor measures of movement (total: 75). For each motor task, five or more biomechanical parameters were measured twice. The results were compared between patients with PD and HC.

RESULTS

Fifty-eight objective motor measures significantly differed between patients with PD and HC; among these, 32 demonstrated relevant discrimination power (Cohen's d > 0.8). The test-retest reliability was excellent in patients with PD (median ICC = 0.85 right limbs, 0.91 left limbs) and HC (median ICC = 0.78 right limbs, 0.82 left limbs).

CONCLUSION

In a supervised environment, the SH-SF device provides motor measures with good results in terms of reliability and discriminant ability. The reliability of SH-SF measurements should be evaluated in an unsupervised home setting in future studies.

The Cholinergic Brain in Parkinson's Disease

The central cholinergic system includes the basal forebrain nuclei, mainly projecting to the cortex, the mesopontine tegmental nuclei, mainly projecting to the thalamus and subcortical structures, and other groups of projecting neurons and interneurons. This system regulates many functions of human behavior such as cognition, locomotion, and sleep. In Parkinson's disease (PD), disruption of central cholinergic transmission has been associated with cognitive decline, gait problems, freezing of gait (FOG), falls, REM sleep behavior disorder (RBD), neuropsychiatric manifestations, and olfactory dysfunction. Neuropathological and neuroimaging evidence suggests that basal forebrain pathology occurs simultaneously with nigrostriatal denervation, whereas pathology in the pontine nuclei may occur before the onset of motor symptoms. These studies have also detailed the clinical implications of cholinergic dysfunction in PD. Degeneration of basal forebrain nuclei and consequential cortical cholinergic denervation are associated with and may predict the subsequent development of cognitive decline and neuropsychiatric symptoms. Gait problems, FOG, and falls are associated with a complex dysfunction of both pontine and basal forebrain nuclei. Olfactory impairment is associated with cholinergic denervation of the limbic archicortex, specifically hippocampus and amygdala. Available evidence suggests that cholinergic dysfunction, alongside failure of the dopaminergic and other neurotransmitters systems, contributes to the generation of a specific set of clinical manifestations. Therefore, a "cholinergic phenotype" can be identified in people presenting with cognitive decline, falls, and RBD. In this review, we will summarize the organization of the central cholinergic system and the clinical correlates of cholinergic dysfunction in PD.

Data-Driven Models for Objective Grading Improvement of Parkinson's Disease

Parkinson's disease (PD) is a progressive disorder of the central nervous system that causes motor dysfunctions in affected patients. Objective assessment of symptoms can support neurologists in fine evaluations, improving patients' quality of care. Herein, this study aimed to develop data-driven models based on regression algorithms to investigate the potential of kinematic features to predict PD severity levels. Sixty-four patients with PD (PwPD) and 50 healthy subjects of control (HC) were asked to perform 13 motor tasks from the MDS-UPDRS III while wearing wearable inertial sensors. Simultaneously, the clinician provided the evaluation of the tasks based on the MDS-UPDRS scores. One hundred-ninety kinematic features were extracted from the inertial motor data. Data processing and statistical analysis identified a set of parameters able to distinguish between HC and PwPD. Then, multiple feature selection methods allowed selecting the best subset of parameters for obtaining the greatest accuracy when used as input for several predicting regression algorithms. The maximum correlation coefficient, equal to 0.814, was obtained with the adaptive neuro-fuzzy inference system (ANFIS). Therefore, this predictive model could be useful as a decision support system for a reliable objective assessment of PD severity levels based on motion performance, improving patients monitoring over time.

Wearable Sensors for Prodromal Motor Assessment of Parkinson's Disease using Supervised Learning

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. Idiopathic hyposmia (IH), a reduced olfactory sensitivity, is a preclinical marker for the pathology and affects >95% of PD patients. In this paper, SensHand V1 and SensFoot V2, two inertial wearable sensors for upper and lower limbs, were developed to acquire motion data in ten tasks of the MDS-UPDRS III. Fifteen healthy subjects of control, 15 IH people, and 15 PD patients were enrolled. Seventy-one parameters per side were computed by spatiotemporal and frequency data analysis, and the most significant were selected to distinguish among the different classes. Performances of supervised learning algorithms (i.e., Support Vector Machine (SVM), and Random Forest (RF)) were compared on two-group and three-group classification and considering upper and lower limbs separately or together as a full system. Excellent results were obtained for healthy vs. patients classification (accuracy 1.00 for RF, and 0.97 for SVM), and good results were achieved by including IH subjects (0.92 F-measure with RF) within a three-group classification. Overall, the best performances were obtained using the full system with an RF classifier. The system is, thus, suitable to support an objective PD diagnosis. Furthermore, combining motion analysis with a validated olfactory screening test, people at risk for PD can be appropriately analyzed, and subtle changes in motor performance that characterize the prodromal phase and the early PD onset can be identified.

A Wearable System to Objectify Assessment of Motor Tasks for Supporting Parkinson's Disease Diagnosis

Objective assessment of the motor evaluation test for Parkinson’s disease (PD) diagnosis is an open issue both for clinical and technical experts since it could improve current clinical practice with benefits both for patients and healthcare systems. In this work, a wearable system composed of four inertial devices (two SensHand and two SensFoot), and related processing algorithms for extracting parameters from limbs motion was tested on 40 healthy subjects and 40 PD patients. Seventy-eight and 96 kinematic parameters were measured from lower and upper limbs, respectively. Statistical and correlation analysis allowed to define four datasets that were used to train and test five supervised learning classifiers. Excellent discrimination between the two groups was obtained with all the classifiers (average accuracy ranging from 0.936 to 0.960) and all the datasets (average accuracy ranging from 0.953 to 0.966), over three conditions that included parameters derived from lower, upper or all limbs. The best performances (accuracy = 1.00) were obtained when classifying all the limbs with linear support vector machine (SVM) or gaussian SVM. Even if further studies should be done, the current results are strongly promising to improve this system as a support tool for clinicians in objectifying PD diagnosis and monitoring.

Olfactory discrimination in disorders of consciousness: A new sniff protocol

BACKGROUND

The identification of salient stimuli useful for rehabilitation purposes is important in patients with disorders of consciousness (DOC): among these, olfactory stimuli might play an important role due to the functional coupling between olfactory and emotional processing. However, a high percentage of post brain injury patients present anosmia.

AIMS OF THE STUDY

The aim of this pilot research is to present an innovative approach to test olfactory functions at the bedside using four selected odors in patients with DOC.

METHODS

Sixteen patients with DOC were tested with two assessment techniques the new olfactory discrimination protocol (ODP) and a functional magnetic resonance imaging paradigm to evaluate olfactory neural process. The Frequentist and Bayesian methods were used to analyze reliability properties of the new tool.

RESULTS

Analysis showed a good agreement between assessment techniques and a substantial test-retest reliability of the ODP. Cohen's Ks were equal to 0.814 (95% CI = 0.471, 1) and 0.607 (0.118; 1) respectively, using the Frequentist approach, while they were 0.762 (95% HPD = 0.470; 0.966) and 0.650 (0.320; 0.913) with the Bayesian approach in the 11 patients analyzed.

CONCLUSIONS

Despite the limits of this preliminary research, the ODP can be useful for clinicians for the preliminary assessment of the olfactory discrimination in patients with DOC.

Objective assessment of blinking and facial expressions in Parkinson's disease using a vertical electro-oculogram and facial surface electromyography

OBJECTIVE

Hypomimia is a common and early symptom of Parkinson's disease (PD), which reduces the ability of PD patients to manifest emotions. Currently, it is visually evaluated by the neurologist during neurological examinations for PD diagnosis, as described in task 3.2 of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Since such an evaluation is semi-quantitative and affected by inter-variability, this paper aims to measure the physiological parameters related to eye blink and facial expressions extracted from a vertical electro-oculogram (VEOG) and facial surface electromyography (fsEMG) to differentiate PD patients from healthy control subjects (HCs).

APPROACH

The spontaneous eye blink rate-minute (sEBR), its maximum amplitude (BMP), and facial cutaneous muscle activity were measured in 24 PD patients and 24 HCs while the subjects looked at a visual-tester composed of three main parts: static vision, dynamic vision and reading silently. Specificity and sensitivity for each parameter were calculated.

MAIN RESULTS

The VEOG and the fsEMG allowed the identification of some parameters related to eye blink and facial expressions (i.e. sEBR, BMP, frontal and peribuccal muscular activities), being able to distinguish between PD patients and HCs with high sensitivity and specificity.

SIGNIFICANCE

The demonstration that the combination of parameters related to eye blink and facial expressions can discriminate (with high accuracy) between PD patients versus HCs, thus resulting in a useful tool to support the neurologist in objective assessment of hypomimia for improving PD diagnosis.

Hyposmia in a simple smell test is associated with accelerated cognitive decline in early Parkinson's disease

OBJECTIVES

Olfactory dysfunction has been related to cognitive deficits in Parkinson's disease (PD), but evidence is conflicting and little is known about the relationship between these symptoms in early PD. Our objective was to study the association between smell deficits measured with a simple odor identification test at diagnosis of PD and the subsequent risk of cognitive decline.

MATERIALS & METHODS

One hundred and ninety two PD patients from a population-based study were examined at time of diagnosis, before initiation of dopaminergic treatment, with follow-up of 177 patients after 3 years, 162 patients after 5 years and 146 patients after 7 years. Cognitive function was assessed repeatedly with tests of global cognition, verbal memory, visuospatial abilities, processing speed, and executive function. Olfactory function was tested with a simple odor identification test at baseline. Associations between outcome measures and hyposmia were assessed by linear mixed effects models.

RESULTS

After 7 years, there were significant differences in global cognition (B: 1.96 (95% CI: 0.68, 3.24), P = 0.0031), verbal memory including immediate recall (B: 5.36 (95% CI: 2.04, 8.67), P = 0.0018) and delayed recall (B: 1.55 (95% CI: 0.51, 2.59), P = 0.0041) and word reading speed (B: 6.90 (95% CI: 2.17, 11.63), P = 0.0048) between hyposmic and normosmic PD patients.

CONCLUSIONS

The decline of cognitive function in early PD is more rapid in patients with hyposmia at diagnosis, compared to normosmic ones. A simple smell test may contribute to identify patients at risk of accelerated decline in global cognition, verbal memory, and processing speed within the first 7 years from diagnosis.

Is Parkinson's Disease a Neurodevelopmental Disorder and Will Brain Organoids Help Us to Understand It?

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. The incidence of PD cases increases with age, accordingly classically PD is considered to be an age-associated neurodegenerative disease. In this review, the hypothesis that PD is actually a neurodevelopmental disorder that is compensated for a long time will be discussed. However, patients who suffer from PD typically do not show symptoms early in their lives. This implies that, if the hypothesis that PD has a significant neurodevelopmental component is correct, the developmental defects are compensated for a long time. Furthermore, these developmental defects might not causally lead to the disease but increase the susceptibility for disease onset after a "second hit." In this logic, deregulated developmental processes might represent the "first hit." Even a minor developmental defect could lead to a reduced compensatory capacity or reduced fault tolerance of the entire system. In such a case of an already imbalanced system one or more additional hits could perturb the entire system sufficiently to bring it out of balance and lead to the pathology and symptoms which we classify as PD. However, if the developmental hypothesis and the "multiple hit" hypothesis are correct, an early diagnosis of these developmental defects might allow the start of a therapy for at-risk individuals before disease pathology becomes severe and before symptoms occur. Modern stem cell technologies, including the generation of personalized brain organoids, might play an important role in these strategies.