Characterizing motor subtypes of Parkinson’s disease (PD) is an important aspect of clinical care that is useful for prognosis and medical management. Although all PD cases involve the loss of dopaminergic neurons in the brain, individual cases may present with different combinations of motor signs, which may indicate differences in underlying pathology and potential response to treatment. However, the conventional method for distinguishing PD motor subtypes involves resource-intensive physical examination by a movement disorders specialist. Moreover, the standardized rating scales for PD rely on subjective observation, which requires specialized training and unavoidable inter-rater variability. In this work, we propose a system that uses machine learning models to automatically and objectively identify some PD motor subtypes, specifically Tremor-Dominant (TD) and Postural Instability and Gait Difficulty (PIGD), from 3D kinematic data recorded during walking tasks for patients with PD (MDS-UPDRS-III Score, 34.7 ± 10.5, average disease duration 7.5 ± 4.5 years). This study demonstrates a machine learning model utilizing kinematic data that identifies PD motor subtypes with a 79.6% F1 score (N = 55 patients with parkinsonism). This significantly outperformed a comparison model using classification based on gait features (19.8% F1 score). Variants of our model trained to individual patients achieved a 95.4% F1 score. This analysis revealed that both temporal, spectral, and statistical features from lower body movements are helpful in distinguishing motor subtypes. Automatically assessing PD motor subtypes simply from walking may reduce the time and resources required from specialists, thereby improving patient care for PD treatments. Furthermore, this system can provide objective assessments to track the changes in PD motor subtypes over time to implement and modify appropriate treatment plans for individual patients as needed.
Background: Individuals with Parkinson's disease (PD) are at increased risk for falls, which lead to substantial morbidity and mortality. Understanding the motor and non-motor impairments associated with falls in PD is critical to informing prevention strategies. In addition to motor symptoms, individuals with PD exhibit non-motor deficits, including impaired set shifting, an aspect of executive function related to cognitive flexibility that can be measured quickly with the Trailmaking Test.
Research question: To determine whether impaired set shifting is associated with fall history in people with and without PD. Methods: We examined associations between set shifting, PD status, and fall history (≥1 falls in the previous 6 months) in data from PD patients (n = 65) with and without freezing of gait (FOG) and community-dwelling neurologically-normal older adults (NON-PD) (n = 73) who had participated in our rehabilitation studies.
Results: Impaired set shifting was associated with previous falls after controlling for age, sex, overall cognitive function, PD status, FOG, and PD disease duration (OR = 1.29 [1.03–1.60]; P = 0.02). Consistent with literature, PD and FOG were also independently associated with increased fall prevalence (PD OR = 4.15 [95% CI 1.65–10.44], P < 0.01; FOG OR = 3.63 [1.22–10.80], P = 0.02). Although the strongest associations between set shifting and falling were observed among PD without FOG (OR = 2.11) compared to HOA (OR = 1.14) and PD with FOG (OR = 1.46), no statistically-significant differences were observed across groups.
SIGNIFICANCE. Impaired set shifting is associated with previous falls in older adults with and without PD. Set shifting may be useful to include in fall risk assessments, particularly when global cognitive measures are within reference limits.
Study objectives included testing whether presumed levodopa-unresponsive freezing of gait (FOG) in Parkinson's disease (PD) actually persists in the presence of adequate dopaminergic dosing and to investigate whether the presence of other parkinsonian features and their responsiveness to therapy varies across patients without FOG (NO-FOG), with levodopa-responsive FOG (OFF-FOG), and with levodopa-unresponsive FOG (ONOFF-FOG). Fifty-five PD patients completed levodopa challenges after >12-h OFF with supratherapeutic doses of dopaminergic medications. Observed responses in FOG, measured with MDS-UPDRS-III during the patient reported full "ON", were used to classify them as NO-FOG, OFF-FOG, or ONOFF-FOG. Serum levodopa levels were measured. Only those with ≥20% improvement in MDS-UPDRS-III score were included in analyses. Levodopa challenge was sufficient to bring about a full "ON" state with ≥20% improvement in 45 patients. Levodopa-equivalent-dose utilized was 142 ± 56% of patients' typical morning doses. Overall, 19/45 patients exhibited FOG in the full "ON" state (ONOFF-FOG), 11 were classified as OFF-FOG, and 15 NO-FOG. Linear mixed models revealed a highly significant association between serum levodopa level and total MDS-UPDRS-III score that was similar across groups. The ONOFF-FOG group exhibited significantly higher New-FOG-questionnaire and MDS-UPDRS-II scores compared to the OFF-FOG group. Among MDS-UPDRS-III subdomains significant effects of group (highest in ONOFF-FOG) were identified for other axial parkinsonian features. We found that FOG can persist in the full "ON" state brought about by ample dopaminergic dosing in PD. Other axial measures can also be levodopa-unresponsive among those with ONOFF-FOG only. These data provide evidence that ONOFF-FOG is distinct from responsive freezing.
Leg rigidity is associated with frequent falls in people with Parkinson’s disease (PD), suggesting a potential role in functional balance and gait impairments. Changes in the neural state due to secondary tasks, e.g., activation maneuvers, can exacerbate (or “activate”) rigidity, possibly increasing the risk of falls. However, the subjective interpretation and coarse classification of the standard clinical rigidity scale has prohibited the systematic, objective assessment of resting and activated leg rigidity. The pendulum test is an objective diagnostic method that we hypothesized would be sensitive enough to characterize resting and activated leg rigidity. We recorded kinematic data and electromyographic signals from rectus femoris and biceps femoris during the pendulum test in 15 individuals with PD, spanning a range of leg rigidity severity. From the recorded data of leg swing kinematics, we measured biomechanical outcomes including first swing excursion, first extension peak, number and duration of the oscillations, resting angle, relaxation index, maximum and minimum angular velocity. We examined associations between biomechanical outcomes and clinical leg rigidity score. We evaluated the effect of increasing rigidity through activation maneuvers on biomechanical outcomes. Finally, we assessed whether either biomechanical outcomes or changes in outcomes with activation were associated with a fall history. Our results suggest that the biomechanical assessment of the pendulum test can objectively quantify parkinsonian leg rigidity. We found that the presence of high rigidity during clinical exam significantly impacted biomechanical outcomes, i.e., first extension peak, number of oscillations, relaxation index, and maximum angular velocity. No differences in the effect of activation maneuvers between groups with clinically assessed low rigidity were observed, suggesting that activated rigidity may be independent of resting rigidity and should be scored as independent variables. Moreover, we found that fall history was more common among people whose rigidity was increased with a secondary task, as measured by biomechanical outcomes. We conclude that different mechanisms contributing to resting and activated rigidity may play an important yet unexplored functional role in balance impairments. The pendulum test may contribute to a better understanding of fundamental mechanisms underlying motor symptoms in PD, evaluating the efficacy of treatments, and predicting the risk of falls.
Parkinson's disease (PD), an intractable condition impairing motor and cognitive function, is imperfectly treated by drugs and surgery. Two priority issues for many people with PD are OFF-time and cognitive impairment. Even under best medical management, three-fourths of people with PD experience “OFF-time” related to medication-related motor fluctuations, which severely impacts both quality of life and cognition. Cognitive deficits are found even in newly diagnosed people with PD and are often intractable. Our data suggest that partnered dance aerobic exercise (PDAE) reduces OFF-time on the Movement Disorders Society Unified Parkinson Disease Rating Scale-IV (MDS-UPDRS-IV) and ameliorates other disease features, which motivate the PAIRED trial. PDAE provides AE during an improvisational, cognitively engaging rehabilitative physical activity. Although exercise benefits motor and cognitive symptoms and may be neuroprotective for PD, studies using robust biomarkers of neuroprotection in humans are rare. We propose to perform a randomized, controlled trial in individuals with diagnosed mild–moderate PD to compare the efficacy of PDAE vs. walking aerobic exercise (WALK) for OFF-time, cognition, and neuroprotection. We will assess neuroprotection with neuromelanin-sensitive MRI (NM-MRI) and iron-sensitive (R2*) MRI sequences to quantify neuromelanin loss and iron accumulation in substantia nigra pars compacta (SNc). We will use these biomarkers, neuromelanin loss, and iron accumulation, as tools to chart the course of neurodegeneration in patients with PD who have undergone long-term (16 months) intervention. We will randomly assign 102 individuals with mild–moderate PD to 16 months of PDAE or WALK. The 16-month intervention period will consist of Training (3 months of biweekly sessions) and Maintenance (13 months of weekly sessions) phases. We will assess participants at baseline, 3 months (immediately post-Training), and 16 months (immediately post-Maintenance) for OFF-time and behaviorally and physiologically measured cognition. We will acquire NM-MRI and R2* imaging data at baseline and 16 months to assess neuroprotection. We will (1) examine effects of Training and Maintenance phases of PDAE vs. WALK on OFF-time, (2) compare PDAE vs. WALK at 3 and 16 months on behavioral and functional MRI (fMRI) measures of spatial cognition, and (3) compare PDAE vs. WALK for effects on rates of neurodegeneration.
Background and Purpose: The objectives of this pilot study were to (1) evaluate the feasibility and investigate the efficacy of a 3-week, high-volume (450 minutes per week) Adapted Tango intervention for community-dwelling individuals with mild-moderate Parkinson disease (PD) and (2) investigate the potential efficacy of Adapted Tango in modifying electromyographic (EMG) activity and center of body mass (CoM) displacement during automatic postural responses to support surface perturbations. Methods: Individuals with PD (n = 26) were recruited for highvolume Adapted Tango (15 lessons, 1.5 hour each over 3 weeks). Twenty participants were assessed with clinical balance and gait measures before and after the intervention. Nine participants were also assessed with support-surface translation perturbations. Results: Overall adherence to the intervention was 77%. At posttest, peak forward CoM displacement was reduced (4.0 ± 0.9 cm, pretest, vs 3.7 ± 1.1 cm, posttest; P = 0.03; Cohen's d = 0.30) and correlated to improvements on Berg Balance Scale (p = .0.68; P = 0.04) and Dynamic Gait Index (p =.0.75; P = 0.03). Overall antagonist onset time was delayed (27 ms; P = 0.02; d = 0.90) and duration was reduced (56 ms, .39%, P = 0.02; d = 0.45). Reductions in EMG magnitude were also observed (P < 0.05). Discussion and Conclusions: Following participation in Adapted Tango, changes in kinematic and some EMG measures of perturbation responses were observed in addition to improvements in clinical measures. We conclude that 3-week, high-volume Adapted Tango is feasible and represents a viable alternative to longer duration adapted dance programs.
Background and Objective
The role of muscle rigidity as an etiological factor of falls in Parkinson's disease (PD) is poorly understood. Our objective was to determine whether lower leg rigidity was differentially associated with frequent falls in PD compared to upper limb, neck, and total rigidity measures.
Methods
We examined the associations between Unified Parkinson's Disease Rating Scale–Part III (motor) rigidity subscores and the history of monthly or more frequent falls in 216 individuals with PD (age, 66 ± 10 years; 36% female; disease duration, 7 ± 5 years) with logistic regression.
Results
A total of 35 individuals were frequent fallers. Significant associations were identified between lower limb rigidity and frequent falls (P = 0.01) after controlling for age, sex, PD duration, total Unified Parkinson's Disease Rating Scale– Part III score, and presence of freezing of gait. No significant associations (P ≥ 0.14) were identified for total, arm, or neck rigidity.
Conclusion
Lower limb rigidity is related to frequent falls in people with PD. Further investigation may be warranted into how parkinsonian rigidity could cause falls.
Background: Abnormal antagonist leg muscle activity could indicate increased muscle co-contraction and clarify mechanisms of balance impairments in Parkinson's disease (PD). Prior studies in carefully selected patients showed PD patients demonstrate earlier, longer, and larger antagonist muscle activation during reactive balance responses to perturbations. Research question: Here, we tested whether antagonist leg muscle activity was abnormal in a group of PD patients who were not selected for phenotype and most of whom had volunteered for exercise-based rehabilitation. Methods: We compared antagonist activation during reactive balance responses to multidirectional support-surface translation perturbations in 31 patients with mild-moderate PD (age 68±9; H&Y 1-3; UPDRS-III 32±10) and 13 matched individuals (age 65±9). We quantified modulation of muscle activity (i.e., the ability to activate and inhibit muscles appropriately according to the perturbation direction) using modulation indices (MI) derived from minimum and maximum EMG activation levels observed across perturbation directions. Results: Antagonist leg muscle activity was abnormal in unselected PD patients compared to controls. Linear mixed models identified significant associations between impaired modulation and PD (P<0.05) and PD severity (P<0.01); models assessing the entire sample without referencing PD status identified associations with balance ability (P<0.05), but not age (P = 0.10). Significance: Antagonist activity is increased during reactive balance responses in PD patients who are not selected on phenotype and are candidates for exercise-based rehabilitation. This activity may be a mechanism of balance impairment in PD and a potential rehabilitation target or outcome measure.
Recent research suggests that the nervous system controls muscles by activating flexible combinations of muscle synergies to produce a wide repertoire of movements. Muscle synergies are like building blocks, defining characteristic patterns of activation across multiple muscles that may be unique to each individual, but perform similar functions. The identification of muscle synergies has strong implications for the organization and structure of the nervous system, providing a mechanism by which task-level motor intentions are translated into detailed, low-level muscle activation patterns. Understanding the complex interplay between neural circuits and biomechanics that give rise to muscle synergies will be crucial to advancing our understanding of neural control mechanisms for movement.
We recently demonstrated that a set of five functional muscle synergies were sufficient to characterize both hindlimb muscle activity and active forces during automatic postural responses in cats standing at multiple postural configurations. This characterization depended critically upon the assumption that the endpoint force vector (synergy force vector) produced by the activation of each muscle synergy rotated with the limb axis as the hindlimb posture varied in the sagittal plane. Here, we used a detailed, 3D static model of the hindlimb to confirm that this assumption is biomechanically plausible: as we varied the model posture, simulated synergy force vectors rotated monotonically with the limb axis in the parasagittal plane (r2=0.94±0.08). We then tested whether a neural strategy of using these five functional muscle synergies provides the same force-generating capability as controlling each of the 31 muscles individually. We compared feasible force sets (FFSs) from the model with and without a muscle synergy organization. FFS volumes were significantly reduced with the muscle synergy organization (F=1556.01, p≪0.01), and as posture varied, the synergy-limited FFSs changed in shape, consistent with changes in experimentally measured active forces. In contrast, nominal FFS shapes were invariant with posture, reinforcing prior findings that postural forces cannot be predicted by hindlimb biomechanics alone. We propose that an internal model for postural force generation may coordinate functional muscle synergies that are invariant in intrinsic limb coordinates, and this reduced-dimension control scheme reduces the set of forces available for postural control.