Gait Event Detection of a Lower Extremity Exoskeleton Robot by an Intelligent IMU

Ding, Shuo; Ouyang, Xiaoping; Liu, Tao; Li, Zhihao; Yang, Huayong

doi:10.1109/jsen.2018.2871328

Cited by 64 publications

(31 citation statements)

References 36 publications

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“…The mid-swing (MSw) phase is marked by the maximum magnitude of the angular velocity signal c [ 16 , 19 , 77 ]. Figure 3 d describes several threshold rules associated with gait phases such as the LR, FF, SW, and ST [ 17 , 90 ]. In addition, it was possible to calculate the gait phases by adaptive threshold lines for locating the peaks of the shank angular rate [ 91 ].…”

Section: Gait Detection Methodsmentioning

confidence: 99%

“…The simplest computation methods of the gait detection are the threshold values. There are different types of threshold algorithms as a set of value rules that figures out certain characteristics of the gait phases or events [ 9 , 10 , 11 , 12 , 13 , 15 , 90 ], time-frequency analysis method based on thresholding values [ 18 , 19 , 20 , 21 , 92 ], or a peak heuristic algorithms which is also a branch of the threshold method in case the derivative passes through zero [ 16 , 19 , 23 , 77 , 93 ]. From the sensor signals, the shank angular velocity signal of the sagittal plane shows clearly two negative peaks at the IC and FO events, this is the simple rule to determine IC and FO events with a high accuracy of detection [ 11 , 19 , 79 , 82 ].…”

Section: Gait Detection Methodsmentioning

confidence: 99%

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A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses

Dong

Cao

et al. 2020

Sensors

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Fast and accurate gait phase detection is essential to achieve effective powered lower-limb prostheses and exoskeletons. As the versatility but also the complexity of these robotic devices increases, the research on how to make gait detection algorithms more performant and their sensing devices smaller and more wearable gains interest. A functional gait detection algorithm will improve the precision, stability, and safety of prostheses, and other rehabilitation devices. In the past years the state-of-the-art has advanced significantly in terms of sensors, signal processing, and gait detection algorithms. In this review, we investigate studies and developments in the field of gait event detection methods, more precisely applied to prosthetic devices. We compared advantages and limitations between all the proposed methods and extracted the relevant questions and recommendations about gait detection methods for future developments.

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Section: Gait Detection Methodsmentioning

confidence: 99%

Section: Gait Detection Methodsmentioning

confidence: 99%

A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses

Dong

Cao

et al. 2020

Sensors

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“…Inertial measurement unit (combination of accelerometers, gyroscopes, and magnetometers) is widely used in the field of robotics to help localization algorithms. The received data can be analyzed: motion measurement of robotics arm or mobile robots [12,13], tracking people or robotic systems [14,15], gait analysis [16,17], and inertial navigation or positioning for mobile robots [18,19]. Its affordability and ease of use on multiple robotic platforms make its integration in robot swarm possible [20].…”

Section: Related Workmentioning

confidence: 99%

Toward a robot swarm protecting a group of migrants

Vaidis

Otis

2020

Intel Serv Robotics

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Different geopolitical conflicts of recent years have led to mass migration of several civilian populations. These migrations take place in militarized zones, indicating real danger contexts for the populations. Indeed, civilians are increasingly targeted during military assaults. Defense and security needs have increased; therefore, there is a need to prioritize the protection of migrants. Very few or no arrangements are available to manage the scale of displacement and the protection of civilians during migration. In order to increase their security during mass migration in an inhospitable territory, this article proposes an assistive system using a team of mobile robots, labeled a rover swarm that is able to provide safety area around the migrants. We suggest a coordination algorithm including CNN and fuzzy logic that allows the swarm to synchronize their movements and provide better sensor coverage of the environment. Implementation is carried out using on a reduced scale rover to enable evaluation of the functionalities of the suggested software architecture and algorithms. Results bring new perspectives to helping and protecting migrants with a swarm that evolves in a complex and dynamic environment.

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“…Firstly, FSRs are not cost-effective [21]. Secondly, FSRs are prone to breakage via fatigue stress because the electrodes directly bear alternating load induced by the external force applied to the ultra-thin sensor [10]. Thirdly, the drift and hysteresis error of FSRs is ten to one hundred times higher than that of the load cell [22].…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, gait monitoring plays an important role in athletic training to help athletes improve their performance [4,5] and in the gait design and control of bipedal humanoid robots [6,7]. In addition, gait phase is broadly investigated in the field of wearable exoskeleton robots [8,9], because only when the rotation movement of the exoskeleton’s joints changes reasonably with the human gait can it provide favorable walking assistance and comfort for the wearer [10].…”

Section: Introductionmentioning

confidence: 99%

Flexible Insole Sensors with Stably Connected Electrodes for Gait Phase Detection

Heng

Pang

et al. 2019

Sensors

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Gait analysis is an important assessment tool for analyzing vital signals collected from individuals and for providing physical information of the human body, and it is emerging in a diverse range of application scenarios, such as disease diagnosis, fall prevention, rehabilitation, and human–robot interaction. Herein, a kind of surface processed conductive rubber was designed and investigated to develop a pressure-sensitive insole to monitor planar pressure in a real-time manner. Due to a novel surface processing method, the pressure sensor was characterized by stable contact resistance, simple manufacturing, and high mechanical durability. In the experiments, it was demonstrated that the developed pressure sensors were easily assembled with the inkjet-printed electrodes and a flexible substrate as a pressure-sensitive insole while maintaining good sensing performance. Moreover, resistive signals were wirelessly transmitted to computers in real time. By analyzing sampled resistive data combined with the gait information monitored by a visual-based reference system based on machine learning method (k-Nearest Neighbor algorithm), the corresponding relationship between plantar pressure distribution and lower limb joint angles was obtained. Finally, the experimental validation of the ability to accurately divide gait into several phases was conducted, illustrating the potential application of the developed device in healthcare and robotics.

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Gait Event Detection of a Lower Extremity Exoskeleton Robot by an Intelligent IMU

Cited by 64 publications

References 36 publications

A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses

A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses

Toward a robot swarm protecting a group of migrants

Flexible Insole Sensors with Stably Connected Electrodes for Gait Phase Detection

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