Handling Gait Impairments of Persons with Parkinson’s Disease by Means of Real-Time Biofeedback in a Daily Life Environment

2016 ◽  
pp. 250-261 ◽  
Author(s):  
Alberto Ferrari ◽  
Pieter Ginis ◽  
Alice Nieuwboer ◽  
Reynold Greenlaw ◽  
Andrew Muddiman ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Real Time ◽  
Daily Life ◽  
Gait Impairments

scholarly journals Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson’s Disease patients

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Robbin Romijnders ◽  
Elke Warmerdam ◽  
Clint Hansen ◽  
Julius Welzel ◽  
Gerhard Schmidt ◽  
...  
Keyword(s):  
Older Adults ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Daily Life ◽  
Neurological Diseases ◽  
Detection Performance ◽  
Measurement Unit ◽  
Straight Line ◽  
Optical Motion ◽  
Task Conditions

Abstract Background Identification of individual gait events is essential for clinical gait analysis, because it can be used for diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson’s disease. Previous research has shown that gait events can be detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only from straight-line walking. For use in daily life, the detection performance needs to be evaluated in curved walking and turning as well as in single-task and dual-task conditions. Methods Participants (older adults, people with Parkinson’s disease, or people who had suffered from a stroke) performed three different walking trials: (1) straight-line walking, (2) slalom walking, (3) Stroop-and-walk trial. An optical motion capture system was used a reference system. Markers were attached to the heel and toe regions of the shoe, and participants wore IMUs on the lateral sides of both shanks. The angular velocity of the shank IMUs was used to detect instances of initial foot contact (IC) and final foot contact (FC), which were compared to reference values obtained from the marker trajectories. Results The detection method showed high recall, precision and F1 scores in different populations for both initial contacts and final contacts during straight-line walking (IC: recall $$=$$ = 100%, precision $$=$$ = 100%, F1 score $$=$$ = 100%; FC: recall $$=$$ = 100%, precision $$=$$ = 100%, F1 score $$=$$ = 100%), slalom walking (IC: recall $$=$$ = 100%, precision $$\ge$$ ≥ 99%, F1 score $$=$$ = 100%; FC: recall $$=$$ = 100%, precision $$\ge$$ ≥ 99%, F1 score $$=$$ = 100%), and turning (IC: recall $$\ge$$ ≥ 85%, precision $$\ge$$ ≥ 95%, F1 score $$\ge$$ ≥ 91%; FC: recall $$\ge$$ ≥ 84%, precision $$\ge$$ ≥ 95%, F1 score $$\ge$$ ≥ 89%). Conclusions Shank-mounted IMUs can be used to detect gait events during straight-line walking, slalom walking and turning. However, more false events were observed during turning and more events were missed during turning. For use in daily life we recommend identifying turning before extracting temporal gait parameters from identified gait events.

scholarly journals Overload From Anxiety: A Non-Motor Cause for Gait Impairments in Parkinson’s Disease

2018 ◽  
Vol 30 (1) ◽  
pp. 77-80 ◽  
Author(s):  
Kaylena A. Ehgoetz Martens ◽  
Carolina R.A. Silveira ◽  
Brittany N. Intzandt ◽  
Quincy J. Almeida
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Gait Impairments

scholarly journals Laboratory versus daily life gait characteristics in patients with multiple sclerosis, Parkinson’s disease, and matched controls

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Vrutangkumar V. Shah ◽  
James McNames ◽  
Martina Mancini ◽  
Patricia Carlson-Kuhta ◽  
Rebecca I. Spain ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Neurological Disease ◽  
Inertial Sensors ◽  
Daily Life ◽  
Area Under The Curve ◽  
Gait Characteristics ◽  
Discrete Moment ◽  
Healthy Control

Abstract Background and purpose  Recent findings suggest that a gait assessment at a discrete moment in a clinic or laboratory setting may not reflect functional, everyday mobility. As a step towards better understanding gait during daily life in neurological populations, we compared gait measures that best discriminated people with multiple sclerosis (MS) and people with Parkinson’s Disease (PD) from their respective, age-matched, healthy control subjects (MS-Ctl, PD-Ctl) in laboratory tests versus a week of daily life monitoring. Methods  We recruited 15 people with MS (age mean ± SD: 49 ± 10 years), 16 MS-Ctl (45 ± 11 years), 16 people with idiopathic PD (71 ± 5 years), and 15 PD-Ctl (69 ± 7 years). Subjects wore 3 inertial sensors (one each foot and lower back) in the laboratory followed by 7 days during daily life. Mann–Whitney U test and area under the curve (AUC) compared differences between PD and PD-Ctl, and between MS and MS-Ctl in the laboratory and in daily life. Results  Participants wore sensors for 60–68 h in daily life. Measures that best discriminated gait characteristics in people with MS and PD from their respective control groups were different between the laboratory gait test and a week of daily life. Specifically, the toe-off angle best discriminated MS versus MS-Ctl in the laboratory (AUC [95% CI] = 0.80 [0.63–0.96]) whereas gait speed in daily life (AUC = 0.84 [0.69–1.00]). In contrast, the lumbar coronal range of motion best discriminated PD versus PD-Ctl in the laboratory (AUC = 0.78 [0.59–0.96]) whereas foot-strike angle in daily life (AUC = 0.84 [0.70–0.98]). AUCs were larger in daily life compared to the laboratory. Conclusions Larger AUC for daily life gait measures compared to the laboratory gait measures suggest that daily life monitoring may be more sensitive to impairments from neurological disease, but each neurological disease may require different gait outcome measures.

scholarly journals Neural Control of Walking in People with Parkinsonism

Physiology ◽  
2016 ◽  
Vol 31 (2) ◽  
pp. 95-107 ◽  
Author(s):  
D. S. Peterson ◽  
F. B. Horak
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Postural Control ◽  
Brain Stem ◽  
Neural Control ◽  
Human Locomotion ◽  
Gait Dysfunction ◽  
Gait Impairments

People with Parkinson's disease exhibit debilitating gait impairments, including gait slowness, increased step variability, and poor postural control. A widespread supraspinal locomotor network including the cortex, cerebellum, basal ganglia, and brain stem contributes to the control of human locomotion, and altered activity of these structures underlies gait dysfunction due to Parkinson's disease.

Real-time quantification of resting tremor in the Parkinson's disease

2009 ◽  
Author(s):  
G. Rigas ◽  
A.T. Tzallas ◽  
D.G. Tsalikakis ◽  
S. Konitsiotis ◽  
D.I. Fotiadis
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Real Time ◽  
Resting Tremor

mHealth Technologies towards Parkinson's Disease Detection and Monitoring in Daily Life: A Comprehensive Review

2020 ◽  
pp. 1-1
Author(s):  
Hanbin Zhang ◽  
Chen Song ◽  
Aditya Singh Rathore ◽  
Mingchun Huang ◽  
Yuan Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Daily Life ◽  
Disease Detection ◽  
Comprehensive Review

scholarly journals Nonlinear dynamics and Poincaré sections to model gait impairments in different stages of Parkinson’s disease

2020 ◽  
Vol 100 (4) ◽  
pp. 3253-3276
Author(s):  
P. A. Pérez-Toro ◽  
J. C. Vásquez-Correa ◽  
T. Arias-Vergara ◽  
E. Nöth ◽  
J. R. Orozco-Arroyave
Keyword(s):  
Nonlinear Dynamics ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Poincaré Sections ◽  
Poincare Sections ◽  
Gait Impairments

scholarly journals Real-Time Neurofeedback to Modulate β-Band Power in the Subthalamic Nucleus in Parkinson’s Disease Patients

eNeuro ◽  
2018 ◽  
Vol 5 (6) ◽  
pp. ENEURO.0246-18.2018 ◽  
Author(s):  
Ryohei Fukuma ◽  
Takufumi Yanagisawa ◽  
Masataka Tanaka ◽  
Fumiaki Yoshida ◽  
Koichi Hosomi ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Real Time ◽  
Subthalamic Nucleus ◽  
Band Power
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