scholarly journals Step Length Estimation with Wearable Sensors Using a Switched-Gain Nonlinear Observer

2021 ◽  
Author(s):  
Ali Nouriani ◽  
Robert A McGovern ◽  
Rajesh Rajamani
Keyword(s):  
Inertial Sensors ◽  
Wearable Sensors ◽  
Infrared Camera ◽  
Step Length ◽  
The Body ◽  
Estimation Problem ◽  
Nonlinear Observer ◽  
Length Estimation ◽  
Minimum Number ◽  
Sensor Configuration

This paper focuses on step length estimation using inertial measurement units. Accurate step length estimation has a number of useful health applications, including its use in characterizing the postural instability of Parkinson’s disease patients. Three different sensor configurations are studied using sensors on the shank and/or thigh of a human subject. The estimation problem has several challenges due to unknown measurement bias, misalignment of the sensors on the body and the desire to use a minimum number of sensors. A nonlinear estimation problem is formulated that aims to estimate shank angle, thigh angle, bias parameters of the inertial sensors and step lengths. A nonlinear observer is designed using Lyapunov analysis and requires solving an LMI to find a stabilizing observer gain. It turns out that global stability over the entire operating region can only be obtained by using switched gains, one gain for each piecewise monotonic region of the nonlinear output function. Experimental results are presented on the performance of the nonlinear observer and compared with gold standard reference measurements from an infrared camera capture system. An innovative technique that utilizes three sensors is shown to provide a step length accuracy nearly equal to that of the four-sensor configuration.

Step length estimation using inertial sensors: Evaluation study

2013 ◽  
Vol 37 ◽  
pp. S27 ◽  
Author(s):  
A. Ferrari ◽  
L. Rocchi ◽  
J. Van den Noort ◽  
J. Harlaar
Keyword(s):  
Inertial Sensors ◽  
Step Length ◽  
Evaluation Study ◽  
Length Estimation

Step Length Estimation Methods Based on Inertial Sensors: A Review

2018 ◽  
Vol 18 (17) ◽  
pp. 6908-6926 ◽  
Author(s):  
Luis Enrique Diez ◽  
Alfonso Bahillo ◽  
Jon Otegui ◽  
Timothy Otim
Keyword(s):  
Inertial Sensors ◽  
Step Length ◽  
Estimation Methods ◽  
Length Estimation

Step Length Estimation and Activity Detection in a PDR System Based on a Fuzzy Model with Inertial Sensors

2014 ◽  
pp. 631-645
Author(s):  
Mariana Natalia Ibarra-Bonilla ◽  
Ponciano Jorge Escamilla-Ambrosio ◽  
Juan Manuel Ramirez-Cortes ◽  
Jose Rangel-Magdaleno ◽  
Pilar Gomez-Gil
Keyword(s):  
Inertial Sensors ◽  
Fuzzy Model ◽  
Step Length ◽  
Activity Detection ◽  
Length Estimation

scholarly journals Step Length Estimation Using Handheld Inertial Sensors

Sensors ◽  
2012 ◽  
Vol 12 (7) ◽  
pp. 8507-8525 ◽  
Author(s):  
Valérie Renaudin ◽  
Melania Susi ◽  
Gérard Lachapelle
Keyword(s):  
Inertial Sensors ◽  
Step Length ◽  
Length Estimation

scholarly journals Continuous home monitoring of Parkinson’s disease using inertial sensors: A systematic review

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246528
Author(s):  
Marco Sica ◽  
Salvatore Tedesco ◽  
Colum Crowe ◽  
Lorna Kenny ◽  
Kevin Moore ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Inertial Sensors ◽  
Wearable Sensors ◽  
Home Monitoring ◽  
Relevant Information ◽  
Step Length ◽  
Living Environment ◽  
Free Living ◽  
Gait Impairments

Parkinson’s disease (PD) is a progressive neurological disorder of the central nervous system that deteriorates motor functions, while it is also accompanied by a large diversity of non-motor symptoms such as cognitive impairment and mood changes, hallucinations, and sleep disturbance. Parkinsonism is evaluated during clinical examinations and appropriate medical treatments are directed towards alleviating symptoms. Tri-axial accelerometers, gyroscopes, and magnetometers could be adopted to support clinicians in the decision-making process by objectively quantifying the patient’s condition. In this context, at-home data collections aim to capture motor function during daily living and unobstructedly assess the patients’ status and the disease’s symptoms for prolonged time periods. This review aims to collate existing literature on PD monitoring using inertial sensors while it focuses on papers with at least one free-living data capture unsupervised either directly or via videotapes. Twenty-four papers were selected at the end of the process: fourteen investigated gait impairments, eight of which focused on walking, three on turning, two on falls, and one on physical activity; ten articles on the other hand examined symptoms, including bradykinesia, tremor, dyskinesia, and motor state fluctuations in the on/off phenomenon. In summary, inertial sensors are capable of gathering data over a long period of time and have the potential to facilitate the monitoring of people with Parkinson’s, providing relevant information about their motor status. Concerning gait impairments, kinematic parameters (such as duration of gait cycle, step length, and velocity) were typically used to discern PD from healthy subjects, whereas for symptoms’ assessment, researchers were capable of achieving accuracies of over 90% in a free-living environment. Further investigations should be focused on the development of ad-hoc hardware and software capable of providing real-time feedback to clinicians and patients. In addition, features such as the wearability of the system and user comfort, set-up process, and instructions for use, need to be strongly considered in the development of wearable sensors for PD monitoring.

scholarly journals Towards ecologically valid biomarkers: real-life gait assessment in cerebellar ataxia

2019 ◽  
Author(s):  
Winfried Ilg ◽  
Jens Seemann ◽  
Martin Giese ◽  
Andreas Traschütz ◽  
Ludger Schöls ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Wearable Sensors ◽  
Real Life ◽  
Movement Analysis ◽  
High Sensitivity ◽  
Step Length ◽  
Gait Variability ◽  
Effect Sizes ◽  
Ataxic Gait ◽  
Disease Modifying Drugs

AbstractBACKGROUNDWith disease-modifying drugs on the horizon for degenerative ataxias, motor biomarkers are highly warranted. While ataxic gait and its treatment-induced improvements can be captured in laboratory-based assessments, quantitative markers of ataxic gait in real life will help to determine ecologically meaningful improvements.OBJECTIVESTo unravel and validate markers of ataxic gait in real life by using wearable sensors.METHODSWe assessed gait characteristics of 43 patients with degenerative cerebellar disease (SARA:9.4±3.9) compared to 35 controls by 3 body-worn inertial sensors in three conditions: (1) laboratory-based walking; (2) supervised free walking; (3) real-life walking during everyday living (subgroup n=21). Movement analysis focussed on measures of movement smoothness and spatio-temporal step variability.RESULTSA set of gait variability measures was identified which allowed to consistently identify ataxic gait changes in all three conditions. Lateral step deviation and a compound measure of step length categorized patients against controls in real life with a discrimination accuracy of 0.86. Both were highly correlated with clinical ataxia severity (effect size ρ=0.76). These measures allowed detecting group differences even for patients who differed only 1 point in the SARAp&g subscore, with highest effect sizes for real-life walking (d=0.67).CONCLUSIONSWe identified measures of ataxic gait that allowed not only to capture the gait variability inherent in ataxic gait in real life, but also demonstrate high sensitivity to small differences in disease severity - with highest effect sizes in real-life walking. They thus represent promising candidates for quantitative motor markers for natural history and treatment trials in ecologically valid contexts.

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