Fariborz Rahimi1, Carina Bee2, Christian Duval3, Patrick Boissy4, Roderick Edwards5, Mandar Jog2. 1. London Health Sciences Centre, Department of Clinical Neurological Sciences, ON, Canada Department of Electrical Engineering, University of Bonab, Bonab, Iran. 2. London Health Sciences Centre, Department of Clinical Neurological Sciences, ON, Canada. 3. Centre de recherche Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada. 4. Department of Surgery, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada. 5. Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada.
Abstract
BACKGROUND: Functional motor impairments including mobility are major reasons for clinical intervention and medication adjustment in symptomatic therapy for Parkinson's disease (PD). Outcome measures used to assess the impact of medication are mostly based on patients' memory or diaries which, considering the gaps between visits, are neither objective nor very reliable. OBJECTIVE: Investigating the feasibility of using movement features extracted from ecological whole-body kinematics recordings to measure the quantitative and qualitative changes in multiple aspects of mobility after medication changes in PD. METHODS: Eleven patients with PD (PwPD) performed mobility tasks in their own home, wearing a full body wireless inertial sensing based motion capture system. Three scripted walking tasks (walking, fast walking, and walk turns) were examined at baseline and two weeks after medication changes. Clinical scales, including investigator-rated clinical global impression of improvement (CGI-I), were collected at both visits. RESULTS: Out of 59 recorded body joint variables, five were identified as pertinent. Changes were represented in vector space as a plot of mean versus peak amplitude. Regression analysis was used to predict clinical improvement or worsening based on these vector features. The predictors were able to explain (>98.5% of variance) patients' clinical global impression of improvement, thus correctly predicting 5 cases of improvement and 2 cases of worsening. CONCLUSIONS: This study provided a method of extracting clinically meaningful reports from ecological kinematic data showing changes after drug adjustments. The results are presented using a novel concept called change space that may be more understandable for clinical staff.
BACKGROUND: Functional motor impairments including mobility are major reasons for clinical intervention and medication adjustment in symptomatic therapy for Parkinson's disease (PD). Outcome measures used to assess the impact of medication are mostly based on patients' memory or diaries which, considering the gaps between visits, are neither objective nor very reliable. OBJECTIVE: Investigating the feasibility of using movement features extracted from ecological whole-body kinematics recordings to measure the quantitative and qualitative changes in multiple aspects of mobility after medication changes in PD. METHODS: Eleven patients with PD (PwPD) performed mobility tasks in their own home, wearing a full body wireless inertial sensing based motion capture system. Three scripted walking tasks (walking, fast walking, and walk turns) were examined at baseline and two weeks after medication changes. Clinical scales, including investigator-rated clinical global impression of improvement (CGI-I), were collected at both visits. RESULTS: Out of 59 recorded body joint variables, five were identified as pertinent. Changes were represented in vector space as a plot of mean versus peak amplitude. Regression analysis was used to predict clinical improvement or worsening based on these vector features. The predictors were able to explain (>98.5% of variance) patients' clinical global impression of improvement, thus correctly predicting 5 cases of improvement and 2 cases of worsening. CONCLUSIONS: This study provided a method of extracting clinically meaningful reports from ecological kinematic data showing changes after drug adjustments. The results are presented using a novel concept called change space that may be more understandable for clinical staff.
Authors: Jorge Posada-Ordax; Julia Cosin-Matamoros; Marta Elena Losa-Iglesias; Ricardo Becerro-de-Bengoa-Vallejo; Laura Esteban-Gonzalo; Carlos Martin-Villa; César Calvo-Lobo; David Rodriguez-Sanz Journal: J Clin Med Date: 2021-04-21 Impact factor: 4.241
Authors: Daniel Collado-Mateo; José C Adsuar; Pedro R Olivares; Francisco J Dominguez-Muñoz; Cristina Maestre-Cascales; Narcis Gusi Journal: PeerJ Date: 2016-02-01 Impact factor: 2.984
Authors: Alberto J Espay; Paolo Bonato; Fatta B Nahab; Walter Maetzler; John M Dean; Jochen Klucken; Bjoern M Eskofier; Aristide Merola; Fay Horak; Anthony E Lang; Ralf Reilmann; Joe Giuffrida; Alice Nieuwboer; Malcolm Horne; Max A Little; Irene Litvan; Tanya Simuni; E Ray Dorsey; Michelle A Burack; Ken Kubota; Anita Kamondi; Catarina Godinho; Jean-Francois Daneault; Georgia Mitsi; Lothar Krinke; Jeffery M Hausdorff; Bastiaan R Bloem; Spyros Papapetropoulos Journal: Mov Disord Date: 2016-04-29 Impact factor: 10.338