Article
Clinical Neurology
Peter C. Fino, Margaret M. Weightman, Leland E. Dibble, Mark E. Lester, Carrie W. Hoppes, Lucy Parrington, Jorge Arango, Alicia Souvignier, Holly Roberts, Laurie A. King
Summary: This study aims to evaluate the diagnostic accuracy, predictive capacity, and responsiveness to rehabilitation of objective dual-task turning measures within an mTBI population. Through two phases, the researchers will explore the potential new guidance and tools these measures can provide for clinical decisions in individuals with mTBI.
FRONTIERS IN NEUROLOGY
(2021)
Article
Clinical Neurology
Angelo Antonini, Heinz Reichmann, Giovanni Gentile, Michela Garon, Chiara Tedesco, Anika Frank, Bjoern Falkenburger, Spyridon Konitsiotis, Konstantinos Tsamis, Georgios Rigas, Nicholas Kostikis, Adamantios Ntanis, Constantinos Pattichis
Summary: This article describes the results of two clinical studies validating the performance of a new wearable monitoring device, PDMonitor, in detecting Parkinson's disease-related motor symptoms. The studies demonstrated high accuracy and correlation between the severity of symptoms and expert evaluations, confirming the effectiveness of the system as a continuous telemonitoring solution for facilitating treatment decisions in patients with Parkinson's disease.
FRONTIERS IN NEUROLOGY
(2023)
Article
Chemistry, Analytical
Sarah Gonzalez, Paul Stegall, Harvey Edwards, Leia Stirling, Ho Chit Siu
Summary: This study utilized wearable sensor data to train a support vector machine for the recognition of walking and running activities, finding that sensors placed on the lower leg produced higher accuracy. It was also noted that using accelerometers only without electromyography sensors decreased the accuracy of the SVM.
Article
Neurosciences
Anjanibhargavi Ragothaman, Oscar Miranda-Dominguez, Barbara H. Brumbach, Andrew Giritharan, Damien A. Fair, John G. Nutt, Martina Mancini, Fay B. Horak
Summary: This study used objective balance and gait measures to examine associations with ventricular and brain volumes in people with Parkinson's disease (PD). The results showed that smaller subcortical and brainstem volumes were associated with larger sway area in people with PD, while larger ventricle volume was associated with smaller anticipatory postural adjustments in healthy controls. The study also found that multiple subcortical region atrophy may be associated with freezing of gait in PD.
JOURNAL OF PARKINSONS DISEASE
(2022)
Article
Clinical Neurology
Parisa Farzanehfar, Holly Woodrow, Malcolm Horne
Summary: The study found that a high proportion of patients with Parkinson's disease experience motor and non-motor function wearing off, with severity correlated to factors such as disease duration, baseline MDS-UPDRS (motor component), Percent Time in Bradykinesia, Levodopa Equivalent Daily Dose, frequency of Levodopa doses, and age of onset. Patients with more severe wearing off experienced worse motor and non-motor symptoms, resulting in lower quality of life. Quality of life significantly improved in patients with Parkinson's disease when wearing off was treated.
JOURNAL OF NEUROLOGY
(2021)
Article
Clinical Neurology
Hui Wang, Binbin Hu, Juan Huang, Lin Chen, Min Yuan, Xingfu Tian, Ting Shi, Jiahao Zhao, Wei Huang
Summary: The study aimed to analyze the clinical features and gait characteristics of PD patients with fatigue and develop a model to identify fatigue in the early stages of PD. The results showed that PD patients with fatigue had more severe impairment of motor symptoms and fatigue became more pronounced as the disease progressed. Combining clinical characteristics and gait cycle parameters can identify PD patients at high risk of fatigue.
FRONTIERS IN NEUROLOGY
(2023)
Article
Engineering, Multidisciplinary
Shaik Jameer, Hussain Syed
Summary: Systems for recognizing human activities are essential in various fields including elderly care, rehabilitation, and surveillance. The biggest challenge lies in extracting relevant features from sensor data, and existing methods are not capable of handling complex behaviors. This research proposes a deep learning-based system that uses a fuzzy logic-based genetic algorithm for feature extraction and a deep convolutional neural network and long short term memory for classification. The experimental results demonstrate high accuracy in recognizing human actions across different datasets.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Engineering, Biomedical
Fahad Kamran, Kathryn Harrold, Jonathan Zwier, Wendy Carender, Tian Bao, Kathleen H. Sienko, Jenna Wiens
Summary: This study investigates the use of machine learning techniques to automatically extract features from inertial measurement unit data for balance assessment, demonstrating that utilizing unprocessed kinematic data significantly improves the accuracy of balance performance estimation by models.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2021)
Article
Computer Science, Artificial Intelligence
Vunnava Dinesh Babu, K. Malathi
Summary: Deep learning and machine learning researchers face the challenge of big data analytics. Distributed systems are an effective technique for boosting efficiency by distributing experiments across devices and sharing training time. However, feature selection techniques often lead to unstable results, impacting classification accuracy. This paper proposes a new three-stage multi-objective feature selection (TMFS) technique that aims to improve the performance of distributed systems by selecting an optimal subset of features and achieving multiple objectives.
Article
Neurosciences
Shubo Lyu, Andris Freivalds, Danielle Symons Downs, Stephen J. Piazza
Summary: This study aimed to explore whether placing an IMU sensor in a pendant worn around the neck could discriminate between conditions with varying postural stability. The results showed that both the belt-mounted and pendant IMU sensors were effective in discriminating between different balance conditions. Therefore, placing an IMU in a pendant may be a feasible approach for studying and monitoring postural instability.
Article
Environmental Sciences
Liangjie Guo, Junhui Kou, Mingyu Wu
Summary: This study systematically investigated the abilities of accelerometer (ACC)-based measures to assess the stability of working postures. The results show that most ACC-based measures can detect the effects of working postures and load carriage, but perform poorly in detecting the effects of standing surfaces. Machine learning algorithms showed good performance in classifying stable and unstable working postures, with feature set exerting a greater influence on accuracy than sensor configuration.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Chemistry, Analytical
Mitchell Ekdahl, Alex Loewen, Ashley Erdman, Sarp Sahin, Sophia Ulman
Summary: This study evaluates IMUs as an alternative method to measure joint angle range of motion and compares it to optical motion capture. The results suggest that IMUs can be a viable alternative for sport-specific lower-extremity ROM measurement, but the selection of sensor-to-segment calibration methods should be based on the specific tasks and variables of interest.
Article
Genetics & Heredity
Ester Pantaleo, Alfonso Monaco, Nicola Amoroso, Angela Lombardi, Loredana Bellantuono, Daniele Urso, Claudio Lo Giudice, Ernesto Picardi, Benedetta Tafuri, Salvatore Nigro, Graziano Pesole, Sabina Tangaro, Giancarlo Logroscino, Roberto Bellotti
Summary: Parkinson's disease is a disease with increasing incidence and significant health burden, emphasizing the importance of early diagnosis. Blood transcriptomics may be a disruptive technology that can help in the early diagnosis of Parkinson's disease.
Article
Multidisciplinary Sciences
Kasandra Diaz, Elizabeth E. L. Stegemoeller
Summary: The study aimed to investigate muscle activity associated with swallow on the more affected side and less affected side in persons with Parkinson's disease (PD). It also explored the relationship between differences in muscle activity and subjective reports of swallowing impairment and disease severity.
Article
Chemistry, Multidisciplinary
Paola Pierleoni, Sara Raggiunto, Alberto Belli, Michele Paniccia, Omid Bazgir, Lorenzo Palma
Summary: In this study, a continuous monitoring system based on a wearable sensor and gait parameter evaluation algorithm was proposed for movement monitoring in patients with Parkinson's disease. The results showed that the algorithm achieved good accuracy in both laboratory and home environments.
APPLIED SCIENCES-BASEL
(2022)
Article
Neurosciences
Rodrigo Vitorio, Naoya Hasegawa, Patricia Carlson-Kuhta, John G. Nutt, Fay B. Horak, Martina Mancini, Vrutangkumar V. Shah
Summary: This study aimed to identify the best measures to distinguish between individuals with Parkinson's disease and healthy individuals based on dual-task gait and turning costs. The findings suggest that people with Parkinson's disease rely more on executive-attentional resources to control arm swing, foot strike, and turning, but not gait speed. Arm range of motion was found to be the most discriminative measure of dual-task costs between Parkinson's disease patients and healthy individuals.
JOURNAL OF PARKINSONS DISEASE
(2021)
Article
Neurosciences
Vrutangkumar V. Shah, James McNames, Graham Harker, Carolin Curtze, Patricia Carlson-Kuhta, Rebecca Spain, Mahmoud El-Gohary, Martina Mancini, Fay B. Horak
Summary: This study investigated the impact of different gait bout definitions on distinguishing walking quality between individuals with multiple sclerosis (MS) and healthy controls (HC) during daily life monitoring. The results showed that despite significant differences in total number of gait bouts across definitions, there was no difference in discriminating gait quality measures between MS and HC. Thus, gait quality measures in people with MS and controls can be compared across studies using different gait bout definitions with pause lengths ≤ 5 s.
Article
Neurosciences
Naoya Hasegawa, Kas C. Maas, Vrutangkumar V. Shah, Patricia Carlson-Kuhta, John G. Nutt, Fay B. Horak, Tadayoshi Asaka, Martina Mancini
Summary: People with Parkinson's disease and freezing of gait have smaller functional limits of stability compared to non-freezers and healthy controls, indicating task-specific postural impairments. However, individuals with Parkinson's disease, with or without freezing of gait, have similar difficulties standing on an unstable surface compared to healthy controls.
Article
Engineering, Biomedical
Vrutangkumar V. Shah, Carolin Curtze, Martina Mancini, Patricia Carlson-Kuhta, John G. Nutt, Christopher M. Gomez, Mahmoud El-Gohary, Fay B. Horak, James McNames
Summary: This study validated and determined the generalizability of algorithms designed for inertial sensors to detect turns in different directions and account for hesitations. The Discrete Turn Algorithm showed improved accuracy compared to previous algorithms, while the Merged Turn Algorithm was recommended for clinical tasks where single-turn angles are known. Specific metrics were proposed to capture turn hesitations in patients with movement disorders.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2021)
Article
Clinical Neurology
Vrutangkumar V. Shah, Roberto Rodriguez-Labrada, Fay B. Horak, James McNames, Hannah Casey, Kyra Hansson Floyd, Mahmoud El-Gohary, Jeremy D. Schmahmann, Liana S. Rosenthal, Susan Perlman, Luis Velazquez-Perez, Christopher M. Gomez
Summary: This study identified gait variability as the most discriminative feature of SCA, with measures like toe-out angle and double-support time variability showing high sensitivity and specificity. These variability measures were also correlated with disease severity, suggesting their potential utility as clinical trial outcome measures for both manifest and prodromal SCAs.
MOVEMENT DISORDERS
(2021)
Article
Neurosciences
Delaram Safarpour, Marian L. Dale, Vrutangkumar V. Shah, Lauren Talman, Patricia Carlson-Kuhta, Fay B. Horak, Martina Mancini
Summary: This study explored the feasibility of using quantified data from wearable sensors as surrogate measures of MDS-UPDRS rigidity and PIGD subscores. Through both at-home and laboratory assessments of gait and balance, correlations between parameters such as number of walking bouts, turns, and postural sway with MDS-UPDRS subscores were identified. The results showed significant correlation between objective sensor data and clinical scores, paving the way for future larger studies evaluating the use of objective sensor data in supplementing remote MDS-UPDRS assessments.
Article
Chemistry, Analytical
Vrutangkumar V. Shah, Carolin Curtze, Kristen Sowalsky, Ishu Arpan, Martina Mancini, Patricia Carlson-Kuhta, Mahmoud El-Gohary, Fay B. Horak, James McNames
Summary: This study developed an algorithm based on inertial sensors to estimate the total distance walked during a walking test, and tested the algorithm's validity and generalizability in two studies. The results showed that the algorithm accurately estimated the total distance walked and has potential clinical applications.
Article
Chemistry, Analytical
Ishu Arpan, Vrutangkumar V. Shah, James McNames, Graham Harker, Patricia Carlson-Kuhta, Rebecca Spain, Mahmoud El-Gohary, Martina Mancini, Fay B. Horak
Summary: This study investigated the potential of passive monitoring of gait and turning in daily life to identify individuals with multiple sclerosis (PwMS) who are at risk of falls. The study found that objective monitoring of gait and turning can predict future falls, with the pitch at toe-off being the most significant predictor. This suggests that interventions aimed at improving muscle strength and range of motion may benefit individuals at risk of falls.
Article
Clinical Neurology
Vrutangkumar V. Shah, James McNames, Patricia Carlson-Kuhta, John G. Nutt, Mahmoud El-Gohary, Kristen Sowalsky, Martina Mancini, Fay B. Horak
Summary: Using body-worn sensors, digital measures of turning were found to be better at discriminating fallers from non-fallers in people with Parkinson's disease, compared to gait measures. This difference was observed in the off medication state and during daily life.
MOVEMENT DISORDERS CLINICAL PRACTICE
(2023)
Article
Clinical Neurology
Rodrigo Vitorio, Martina Mancini, Patricia Carlson-Kuhta, Fay B. Horak, Vrutangkumar V. Shah
Summary: This study found that considering both clinical factors and objective balance and gait characteristics is important for distinguishing fallers from non-fallers in Parkinson's disease.
PARKINSONISM & RELATED DISORDERS
(2023)
Article
Chemistry, Analytical
Carla Silva-Batista, Graham Harker, Rodrigo Vitorio, Fay B. Horak, Patricia Carlson-Kuhta, Sean Pearson, Jess VanDerwalker, Mahmoud El-Gohary, Martina Mancini
Summary: This study tested the feasibility of using a physical therapist assisted system (Mobility Rehab) with wearable sensors for one session of treadmill training in 10 people with Parkinson's disease (PD). The training significantly improved foot-strike angle, trunk coronal range-of-motion (RoM), and arm swing RoM during overground walking. Participants perceived moderate to excellent effects on their gait. One session of treadmill training with Mobility Rehab is feasible for people with mild-to-moderate PD.
Article
Chemistry, Analytical
Vrutangkumar V. Shah, Barbara H. Brumbach, Sean Pearson, Paul Vasilyev, Edward King, Patricia Carlson-Kuhta, Martina Mancini, Fay B. Horak, Kristen Sowalsky, James McNames, Mahmoud El-Gohary
Summary: The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity and sleep in daily life. The results showed that Opal Actigraphy demonstrated comparable performance to ActiGraph, supporting its use in research and clinical studies to quantify activity and monitor sleep patterns.
Article
Clinical Neurology
Natalia Mariano Barboza, Martina Mancini, Suhaila Mahmoud Smaili, Fay B. Horak, Patricia Carlson-Kuhta, Rosie Morris, Laurie A. King
Summary: This study compared different aspects of gait and balance between individuals with Parkinson's disease who have normal cognition and those with impaired cognition. The results showed that dynamic balance during gait was more impaired in individuals with impaired cognition. No differences were found in other balance domains.
PARKINSONISM & RELATED DISORDERS
(2023)
Article
Clinical Neurology
Vrutangkumar V. Shah, Rodrigo Vitorio, Naoya Hasegawa, Patricia Carlson-Kuhta, John G. Nutt, Laurie A. King, Martina Mancini, Fay B. Horak
Summary: This study revealed that individuals with and without freezing of gait in Parkinson's disease (PD) show improvements in gait performance after participating in the Agility Boot Camp with Cognitive Challenges (ABC-C) program. The program was effective in improving dual-task gait speed, arm range of motion, and other gait measures in both groups. However, balance performance did not improve. The results suggest that the ABC-C program can benefit individuals with PD, regardless of the presence of freezing of gait.
NEUROREHABILITATION AND NEURAL REPAIR
(2022)
