Search Results (14)

Background: Freezing of gait (FoG) is a common symptom of Parkinson’s disease, especially in its later stages of progression. Characterized by involuntary stopping during normal gait patterns, FoG greatly increases fall risk, reducing quality of life. Given the complex presentation and etiology of FoG, current treatments have proven ineffective in managing episodes. In recent years, machine learning algorithms have been leveraged to derive actionable clinical insights from biomedical datasets. As a manifestation of neuromechanical dysfunction, impending FoG episodes may be characterized through data collected by wearable devices and sensors. Objective: This scoping review evaluates the current landscape of machine and deep learning-derived biomarkers to enhance the personalized management of FoG. Methods: This scoping review was conducted using established methodological frameworks for scoping reviews and is reported in accordance using the PRISMA-ScR checklist. Three databases were queried, with screening yielding 60 studies. Results: Thirty-nine papers reported on deep learning techniques, with the most common architectures being convolutional neural networks and long short-term memory models. Conclusions: Inertial measurement units, which can be worn on various locations, may be a promising modality for practical implementation. To generate closed-loop FoG therapies, algorithms can be integrated into real-time systems like robotic exoskeletons or adaptive deep brain stimulation. Future work in generating datasets from ambulatory devices, as well as distributed computing strategies, may lead to real-time FoG management. Full article

Parkinson’s disease (PD) is the fastest-growing neurodegenerative disease affecting 90 thousand new Americans each year. PD includes motor and non-motor symptoms, resulting in progressive disability and difficulty in completing activities of daily living. Freezing of Gait (FoG) is one of the common disabling symptoms of PD, characterized by difficulties in initiating walking, resulting in gait abnormalities and increased risk of falling (RoF) and fear of falling (FoF). Clinical management of FoG is difficult as it is minimally responsive to both pharmacological and surgical interventions. In fact, these interventions can paradoxically worsen of FoG. Additionally, PD patients with FoG have reported worse health-related quality of life (HR-QoL) due to limitations in mobility, activities of daily living (ADL), bodily discomfort, stigma, and social isolation. Despite its increasing treatment and management of FoG is difficult due to its paroxysmal and heterogeneous nature. Therefore, there is a growing need for effective, evidence-based management and intervention approaches for FoG. Some current techniques used to manage FoG are physical therapy, exercise, gait training, and balance training; however, due to a lack of patient adherence, accessibility concerns, and the need for continuous supervision and individualized feedback, the long-term effectiveness of these interventions remains limited and challenging to achieve in real-world settings. A new promising avenue for managing PD is the use of wearable technology, which can provide audiovisual, via augmented and virtual reality (AR/VR), and tactical cueing to offset FoG, thereby enhancing independence in PD patients. In this comprehensive review, we will provide an overview of the symptoms, monitoring, and treatment of PD, with a focus on the neuroanatomy and treatment of FoG. We will review and critique the extant literature on the use of AR/VR technology in the management of FoG. Finally, the challenges and risks associated with wearable technology in FoG management will also be identified. Full article

The LRRK2+ SAA− cohort of Parkinson’s disease (PD), characterized by the absence of hallmark α-synuclein pathology, remains under-explored. This limits opportunities for early detection and targeted intervention. This study analyzes data from this under-characterized subgroup and compares it with the LRRK2+ SAA+ cohort using longitudinal data from the Parkinson’s Progression Markers Initiative (PPMI). The PPMI dataset includes 115 LRRK2+ patients (70 SAA+, 45 SAA−) across 52 features encompassing clinical assessments, cognitive scores, DaTScan SPECT imaging, and motor severity. DaTScan binding ratios were selected as imaging-based indicators of early dopaminergic loss, while NP3TOT (MDS-UPDRS Part III total score) was used as a gold-standard clinical measure of motor symptom severity. Linear mixed-effects models were then applied to evaluate longitudinal predictors of DaTScan decline and NP3TOT progression, and statistical analyses of group comparisons revealed distinct drivers of symptoms differentiating SAA− from SAA+ patients. In SAA− patients, a decline in DaTScan was significantly associated with thermoregulatory impairment (p-value = 0.019), while NP3TOT progression was predicted by constipation (p-value = 0.030), sleep disturbances (p-value = 0.046), and longitudinal time effects (p-value = 0.043). In contrast, SAA+ patients showed significantly lower DaTScan values compared to SAA− (p-value = 0.0004) and stronger coupling with classical motor impairments, including freezing of gait (p-value = 0.016), rising from a chair (p-value = 0.007), and turning in bed (p-value = 0.016), along with cognitive decline (MoCA clock-hands test, p-value = 0.037). These findings support the hypothesis that LRRK2+ SAA− patients follow a distinct pathophysiological course, where progression is influenced more by autonomic and non-motor symptoms than by typical motor dysfunction. This study establishes a robust, multimodal modeling framework for examining heterogeneity in genetic PD and highlights the utility of combining DaTScan, NP3TOT, and symptom-specific features for early subtype differentiation. These findings have direct clinical implications, as stratifying LRRK2 carriers by SAA status may enhance patient monitoring, improve prognostic accuracy, and guide the design of targeted clinical trials for disease-modifying therapies. Full article

Background: Asymmetrical brain oscillations may be characteristic of Parkinson’s disease (PD). We investigated differences in oscillation asymmetry between individuals with PD and healthy controls and explored associations between the asymmetry and clinical features. Methods: Clinical and resting-state EEG data from 37 patients and 24 controls were cross-sectionally analyzed. EEG asymmetry indices were calculated for the delta, theta, alpha, and beta frequencies in the frontal, central, and parietal regions. Independent t-tests and linear regression models were employed. Results: Patients exhibited lower alpha asymmetry than controls in the parietal region (t(59) = 2.12, p = 0.03). In the frontal alpha asymmetry models, there were associations with time since diagnosis (β = −0.042) and attention/orientation (β = 0.061), and with Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRSIII)-posture (β = 0.136) and MDS-UPDRSIII-rest-tremor persistence (β = −0.111). In the central alpha model, higher asymmetry was associated with the physical activity levels (International Physical Activity Questionnaire) IPAQ-active (β = 0.646) and IPAQ-very active (β = 0.689), (Timed Up and Go) TUG dual-task cost (β = 0.023), MDS-UPDRSII-freezing (β = 0.238), and being male (β = 0.535). In the parietal alpha asymmetry model, MDS-UPDRSII-gait/balance was inversely associated with alpha asymmetry (β = −0.156), while IPAQ-active (β = −0.247) and being male (β = −0.191) were associated with lower asymmetry. Conclusions: Our findings highlight the potential role of alpha asymmetry as a neurophysiological marker of PD’s motor symptoms, mainly rest tremor, gait/balance, freezing, and specific cognitive domains such as attention/orientation. The models stressed the relationship between disease progression and reduced alpha asymmetry. Brazilian Registry of Clinical Trials (RBR-7zjgnrx, 9 June 2022). Full article

Background: Parkinson’s Disease (PD) is a progressive neurodegenerative disorder characterized by motor impairments, including balance deficits, gait disturbances, and postural instability. Given the limitations of pharmacological treatments, alternative rehabilitative strategies such as Argentine Tango (AT) have been explored for their potential benefits in improving mobility and quality of life in individuals with PD. This systematic review evaluates the effectiveness of AT in enhancing balance, gait, and functional mobility in PD patients. Methods: A systematic literature search was conducted across PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Scopus, PEDro, and Web of Science. Studies were included if they were randomized controlled trials (RCTs) assessing the impact of AT on motor outcomes in PD. Data extraction and risk of bias assessment were performed independently by two reviewers using the Risk of Bias 2 (RoB 2) tool. Results: Five randomized controlled trials (RCTs) were included, with sample sizes ranging from 10 to 62 participants and intervention durations varying from 10 weeks to 24 months. AT significantly improved balance (Mini-BESTest, BBS, FRT), gait performance (6MWT, TUG), and mobility compared to usual care or conventional exercise. Some studies also reported psychological benefits, including reduced depressive symptoms and increased balance confidence. However, freezing of gait outcomes were inconclusive, and methodological limitations, such as small sample sizes and inconsistent intervention durations, were noted. Outcomes for freezing of gait (FoG) remained inconclusive due to the variability in assessment methods and inconsistent reporting across studies. Conclusions: AT appears to be an effective rehabilitation strategy for improving balance, gait, and functional mobility in PD. While preliminary evidence suggests additional psychological benefits, larger, high-quality trials are needed to confirm its long-term efficacy and establish standardized intervention protocols. AT may be integrated into multimodal rehabilitation programs to enhance motor and psychosocial outcomes in PD management. However, the small sample sizes of included studies and the heterogeneity in intervention durations limit the generalizability of findings. AT may serve as a structured rehabilitative approach for improving mobility and psychosocial outcomes in PD and could be integrated into community-based or clinical rehabilitation programs. Full article

Background: Progressive supranuclear palsy (PSP) is characterized by early postural instability and gait dysfunction, with frequent falls. Rehabilitation is an important therapeutic approach for motor dysfunction in patients with PSP. However, no conclusions have yet been drawn regarding the beneficial effects of rehabilitation in PSP, including the optimal duration of rehabilitation and differences in treatment effects among PSP subtypes. Herein, we investigated the effects of short-term rehabilitation and separately analyzed the effects on patients with PSP-Richardson’s syndrome (RS) and PSP-progressive gait freezing (PGF). Methods: The participants underwent several therapeutic exercise programs individualized for each participant, performed over 2 weeks. Analysis was performed on 25 patients with PSP-RS and eight with PSP-PGF. Results: Short-term rehabilitation improved the Berg Balance Scale score in both the PSP-RS and PSP-PGF groups, step length on the symptom-dominant side in PSP-RS, the coefficient of variation of step length on the symptom-dominant side, and the stance phase of the Symmetry Index in PSP-PGF. Conclusions: Overall, this 2-week short-term rehabilitation intervention was shown to have beneficial effects on balance in patients with PSP-RS and PSP-PGF. Full article

Freezing of gait is a frequent phenomenon and can be one of the most debilitating motor impairments in Parkinson’s disease, especially in the advanced stages. It is currently defined as a brief episodic absence or any marked reduction in the forward progression of the feet, despite the intention to walk. Greater severity of freezing of gait has been associated with more frequent falls, postural instability, and executive dysfunction. However, botulinum neurotoxin is one of the most widely administered therapies for motor and non-motor symptoms, including freezing of gait, in parkinsonism. To date, the literature has had conflicting results on the use of botulinum toxin in the treatment of freezing of gait in Parkinson’s disease patients. In light of this, we reviewed the findings of past studies that specifically investigated the effects of botulinum toxin on freezing of gait in Parkinson’s disease in order to better understand this issue. Full article

Background and Objectives: This report described two cases with clear longitudinal changes in motor estimation error (difference between the motor imagery and motor execution) and their progression and motor and activities of daily living (ADL) function changes in patients with PD. Materials and Methods: Patient 1 was a 68-year-old man (Hoehn and Yahr [H and Y] stage: IV, diagnosed with PD for 11.8 years) and patient 2 was a 68-year-old woman (H and Y stage: II, diagnosed with PD for 9.6 years). Imagined two-step test (iTST), two-step test (TST), and PD-related assessments (Unified Parkinson’s Disease Rating Scale [UPDRS], and Freezing of Gait Questionnaire [FOGQ]) were assessed at baseline and after 6 months. Motor estimation error was calculated as the iTST distance minus TST distance. Results: In patient 1, motor estimation error was greater after 6 months (baseline: 5.7 [4.8%]/after 6 months: 25.7 cm [26.1%]). Moreover, UPDRS and FOGQ total scores deteriorated after 6 months (UPDRS total: 29/34 point, and FOGQ: 9/16 point). Conversely, in patient 2, motor estimation error did not change notably (−3.6 [7.6%]/−2.5 cm [7.0%]), while UPDRS and FOGQ total scores improved after 6 months (UPDRS total: 17/12 point, and FOGQ: 6/1 point). Conclusions: This report indicated that greater motor estimation error may be associated with declining motor and ADL function and disease progression in patients with PD. Full article

Parkinson’s disease (PD) has become the second most common neurodegenerative condition following Alzheimer’s disease (AD), exhibiting high prevalence and incident rates. Current care strategies for PD patients include brief appointments, which are sparsely allocated, at outpatient clinics, where, in the best case scenario, expert neurologists evaluate disease progression using established rating scales and patient-reported questionnaires, which have interpretability issues and are subject to recall bias. In this context, artificial-intelligence-driven telehealth solutions, such as wearable devices, have the potential to improve patient care and support physicians to manage PD more effectively by monitoring patients in their familiar environment in an objective manner. In this study, we evaluate the validity of in-office clinical assessment using the MDS-UPDRS rating scale compared to home monitoring. Elaborating the results for 20 patients with Parkinson’s disease, we observed moderate to strong correlations for most symptoms (bradykinesia, rest tremor, gait impairment, and freezing of gait), as well as for fluctuating conditions (dyskinesia and OFF). In addition, we identified for the first time the existence of an index capable of remotely measuring patients’ quality of life. In summary, an in-office examination is only partially representative of most PD symptoms and cannot accurately capture daytime fluctuations and patients’ quality of life. Full article

Freezing of gait (FOG), one of the most disabling features of Parkinson’s disease (PD), is a brief episodic absence or marked reduction in stride progression despite the intention to walk. Progressively more people who experience FOG restrict their walking and reduce their level of physical activity. The purpose of this study is to develop and validate a physical mobility task that induces freezing of gait in a controlled environment, employing known triggers of FOG episodes according to the literature. To validate the physical mobility tasks, we recruited 10 volunteers that suffered PD-associated freezing (60.6 ± 7.29 years-old) with new FOG-Q ranging from 12 to 26. The validation of the proposed method was carried out using inertial sensors and video recordings. All subjects were assessed during the OFF and ON medication states. The total number of FOG occurrences during data collection was 144. The proposed tasks were able to trigger 120 FOG episodes, while the TUG test caused 24. The Inertial Measurement Unit (IMU) with accelerometer and gyroscope could not only detect FOG episodes but also allowed us to visualize the three types of FOG: akinesia, festination and trembling in place. Full article

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 establish the best-performing algorithm for the classification of the recorded gait information. The combination of attention-based convolutional and recurrent neural networks algorithms outperformed the other tested algorithms and was individually tested further on the datasets of five subjects and delivered the following averaged results of classification: 98.9% accuracy, 96.8% precision, 97.8% sensitivity, 99.1% specificity and 97.3% F1-score. Moreover, the algorithm’s robustness was also verified with the successful detection of freezing gait episodes in a Parkinson’s disease patient. The results of this study indicate a feasible gait event classification method capable of complete algorithm personalization. Full article

Parkinson’s disease resulting from the degeneration of specific areas of the brain, can cause severely disabling symptoms, such as freezing of gait. Freezing of gait increases the risk of falls through worsening of physical mobility, muscle stiffening, slow uncoordinated movements and often leads to hospitalization with significant worsening of quality of life for such patients. Indeed, older patients are at a significantly higher risk of negative outcomes related to PD. This work focuses on the most recent findings regarding non-invasive intervention and monitoring strategies to counteract the effects of freezing of gait. In addition, several devices can also provide support for diagnosis, treatment, and quality of daily life, especially in older patients with PD. This narrative review describes the current state of the art of devices based on cueing, monitoring and rehabilitation systems. Fifty-seven studies were selected. Overall findings demonstrates that these smart devices can act as a valid aid tools able to: i) learn patient motor habits in order to intervene during a freezing of gait episode, ii) monitor daily conditions, iii) send and store data on disease progression, iv) provide useful information for rehabilitation programs in a clinical or home care environment. These technologies hold excellent prospects for patient treatment tailoring, especially in older patients in home care. Full article

Progressive gait dysfunction is one of the primary motor symptoms in people with Parkinson’s disease (PD). It is generally expressed as reduced step length and gait speed and as increased variability in step time and step length. People with PD also exhibit stooped posture which disrupts gait and impedes social interaction. The gait and posture impairments are usually resistant to the pharmacological treatment, worsen as the disease progresses, increase the likelihood of falls, and result in higher rates of hospitalization and mortality. These impairments may be caused by perceptual deficiencies (poor spatial awareness and loss of temporal rhythmicity) due to the disruptions in processing intrinsic information related to movement initiation and execution which can result in misperceptions of the actual effort required to perform a desired movement and maintain a stable posture. Consequently, people with PD often depend on external cues during execution of motor tasks. Numerous studies involving open-loop cues have shown improvements in gait and freezing of gait (FoG) in people with PD. However, the benefits of cueing may be limited, since cues are provided in a consistent/rhythmic manner irrespective of how well a person follows them. This limitation can be addressed by providing feedback in real-time to the user about performance (closed-loop cueing) which may help to improve movement patterns. Some studies that used closed-loop cueing observed improvements in gait and posture in PD, but the treadmill-based setup in a laboratory would not be accessible outside of a research setting, and the skills learned may not readily and completely transfer to overground locomotion in the community. Technologies suitable for cueing outside of laboratory environments could facilitate movement practice during daily activities at home or in the community and could strongly reinforce movement patterns and improve clinical outcomes. This narrative review presents an overview of cueing paradigms that have been utilized to improve gait and posture in people with PD and recommends development of closed-loop wearable systems that can be used at home or in the community to improve gait and posture in PD. Full article

Osteoarthritis (OA) is the most common joint disorder in the world and is the most frequent cause of walking related disability among older adults in the US, which brings a significant economic burden and reduces quality of life. The initiation and development of OA typically involves degeneration or progressive loss of the structure and function of articular cartilage. Inflammation is one of the major drives of the progression of OA. Dietary polyphenols have been studied for their anti-inflammatory properties and potential anabolic effects on the cartilage cells. Blueberries are widely consumed and are high in dietary polyphenols, therefore regular consumption of blueberries may help improve OA. The purpose of the present study was to examine the effect of freeze dried whole blueberries on pain, gait performance, and inflammation in individuals with symptomatic knee OA. In a randomized, double-blind trial, adults age 45 to 79 with symptomatic knee OA, were randomized to either consume 40 g freeze-dried blueberry powder (n = 33) or placebo powder (n = 30) daily for four months. Blood draws and assessment of pain and gait were conducted at baseline, two months, and four months. Western Ontario McMaster Osteoarthritis Index (WOMAC) questionnaires were used to assess pain and GAITRite^® electronic walkway was used to evaluate gait spatiotemporal parameters. WOMAC total score and sub-groups, including pain, stiffness, and difficulty to perform daily activities decreased significantly in the blueberry treatment group (p < 0.05), but improvement of WOMAC total score and difficulty to perform daily activities were not observed in the placebo group. Normal walking pace single support percentage for both limbs increased (p = or < 0.007), while double support percentage for both limbs decreased in the blueberry treatment group (p = or < 0.003). No significant changes were observed in plasma concentrations of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, IL-10, IL-13, matrix metalloproteinases (MMP)-3, MMP-13, and monocyte chemoattractant protein-1 (MCP-1) in both treatment groups. However, an increasing trend for IL-13 concentration and a decreasing trend in MCP-1 concentration were noted in the blueberry group. The findings of this study suggest that daily incorporation of whole blueberries may reduce pain, stiffness, and difficulty to perform daily activities, while improving gait performance, and would therefore improve quality of life in individuals with symptomatic knee OA. Full article