IMU based detection of freezing of gait and festination in Parkinson's disease

Sijobert, Benoît; Denys, Jennifer; Coste, Christine; Gény, Christian

doi:10.1109/ifess.2014.7036751

Cited by 30 publications

(23 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(OMC) system, which utilizes multiple optical cameras to calculate 3D positions of body joints, is most commonly used to analyze gait phases and has the advantage of providing real-time measures of movement a rapid reaction rate and the ability to measure data close to the human movements even for complex motions [7,9].Over the past few years, a number of wearable inertial measurement unit (IMU) systems have been used to analyze human joint movement in laboratories or in living environments [10]. The IMU system is useful because the system function is verified in the gait analysis of people with disabilities in low cost and non-invasive methods [11][12][13]. In order to increase the universal use of the IMU system, it is very necessary to analyze the accuracy of the IMU system by comparing the results of the gait analysis of the IMU system and the OMC system.…”

mentioning

confidence: 99%

“…Over the past few years, a number of wearable inertial measurement unit (IMU) systems have been used to analyze human joint movement in laboratories or in living environments [10]. The IMU system is useful because the system function is verified in the gait analysis of people with disabilities in low cost and non-invasive methods [11][12][13]. In order to increase the universal use of the IMU system, it is very necessary to analyze the accuracy of the IMU system by comparing the results of the gait analysis of the IMU system and the OMC system.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Yeo

Park

2020

Sensors

View full text Add to dashboard Cite

Inertial measurement unit systems are wearable sensors that can measure the movement of a human in real-time with relatively little space and high portability. The purpose of this study was to investigate the accuracy of the inertial measurement unit (IMU) system for gait analysis by comparing it with measurements obtained using an optical motion capture (OMC) system. To compare the accuracies of these two different motion capture systems, the Spatio-temporal and kinematic parameters were measured in young adults during normal walking. Thirty healthy participants participated in the study. Data were collected while walking 5 strides on a 7 m walkway at a self-selected speed. Results of gait analysis showed that the Spatio-temporal (stride time, stride length, cadence, step length) and kinematic (knee joint peak to peak of movement) parameters were not significantly different in the participant. Spatio-temporal and kinematic parameters of the two systems were compared using the Bland-Altman method. The results obtained showed that the measurements of Spatio-temporal and kinematic parameters of gait by the two systems were similar, which suggested that IMU and OMC systems could be used interchangeably for gait measurements. Therefore, gait analysis performed using the wearable IMU system might efficiently provide gait measurements and enable accurate analysis. (OMC) system, which utilizes multiple optical cameras to calculate 3D positions of body joints, is most commonly used to analyze gait phases and has the advantage of providing real-time measures of movement a rapid reaction rate and the ability to measure data close to the human movements even for complex motions [7,9].Over the past few years, a number of wearable inertial measurement unit (IMU) systems have been used to analyze human joint movement in laboratories or in living environments [10]. The IMU system is useful because the system function is verified in the gait analysis of people with disabilities in low cost and non-invasive methods [11][12][13]. In order to increase the universal use of the IMU system, it is very necessary to analyze the accuracy of the IMU system by comparing the results of the gait analysis of the IMU system and the OMC system. Inertial measurement unit systems use accelerometers, gyroscopes, and magnetometers to provide data on the motion characteristics of joints and segments during various tasks [10]. IMU system can measure human joint movements in real-time and has the advantage of being able to measure in relatively little space and is highly portable compared to the OMC system. However, the disadvantage of the IMU system is that it includes a position drift that may vary over time with lower position accuracy. Position accuracy is a problem because it is determined by constantly integrating acceleration over time to calculate speeds and positions, and this results in cumulative measurement errors. In addition, since the position of the IMU sensors for measuring joint movement does not match the anatomical position of the ...

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Yeo

Park

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…gait assistive devices. For instance, in order to pilot an auditory system based on freezing events detection for Parkinson's disease [23].…”

Section: Discussionmentioning

confidence: 99%

Implementation and Validation of a Stride Length Estimation Algorithm, Using a Single Basic Inertial Sensor on Healthy Subjects and Patients Suffering from Parkinson’s Disease

Sijobert¹,

Benoussaad²,

Denys³

et al. 2015

Health

Self Cite

View full text Add to dashboard Cite

As low cost and highly portable sensors, inertial measurements units (IMU) have become increasingly used in gait analysis, embodying an efficient alternative to motion capture systems. Meanwhile, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gyrometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson's disease (PD). Estimated stride lengths were compared to GAITRite © walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the instantaneous stride length and opens the way to promising applications.

show abstract

“…In future work, we will use information from the sensor to modulate the stimulation in real time, in case of FOG detection, u‐turn or, for example, to adapt the stimulus to gait pattern. Such a sensor may also be used to monitor some gait parameters in order to assess functional improvement .…”

Section: Methodsmentioning

confidence: 99%

Effects of Sensitive Electrical Stimulation‐Based Somatosensory Cueing in Parkinson's Disease Gait and Freezing of Gait Assessment

et al. 2017

Self Cite

View full text Add to dashboard Cite

This study aims to investigate the effect of a somatosensory cueing on gait disorders in subjects with Parkinson's disease (PD). After having performed stepping in place and timed up and go assessing tasks, 13 participants with PD were equipped with an electrical stimulator and an inertial measurement unit (IMU) located under the lateral malleolus on the sagittal plane. Electrodes were positioned under the arch of the foot and electrical stimulation (ES) parameters (five 500 µs/phase charge-balanced biphasic pulses delivered at 200 Hz, repeated four times at 10 Hz) adjusted to deliver a sensitive signal. Online IMU signal was processed in order to trigger ES at heel off detection. Starting from a quiet standing posture, subjects were asked to walk at their preferred speed on a path including 5 m straight line, u-turn, and walk around tasks. Three situations were considered: no stimulation baseline precondition (C0), ES condition (C1), and no stimulation baseline post-condition (C0bis), for eliminating a learning effect possibility. In ES condition (C1) the time to execute the different tasks was globally decreased in all the subjects (n = 13). Participants' results were then grouped regarding whether they experienced freezing of gait (FOG) or not during C0 no stimulation baseline precondition. In "freezer" subjects (n = 9), the time to complete the entire path was reduced by 19%. FOG episodes occurrence was decreased by 12% compared to baseline conditions. This preliminary work showed a positive global effect on gait and FOG in PD by a somatosensory cueing based on sensitive electrical stimulation.

show abstract

IMU based detection of freezing of gait and festination in Parkinson's disease

Cited by 30 publications

References 14 publications

Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Implementation and Validation of a Stride Length Estimation Algorithm, Using a Single Basic Inertial Sensor on Healthy Subjects and Patients Suffering from Parkinson’s Disease

Effects of Sensitive Electrical Stimulation‐Based Somatosensory Cueing in Parkinson's Disease Gait and Freezing of Gait Assessment

Contact Info

Product

Resources

About