May I Keep an Eye on Your Training? Gait Assessment Assisted by a Mobile Robot

Scheidig, Andrea; Jaeschke, Bianca; Schuetz, Benjamin; Trinh, Thanh Q.; Vorndran, Alexander; Mayfarth, Anke; Groß, Horst–Michael

doi:10.1109/icorr.2019.8779369

Cited by 14 publications

(11 citation statements)

References 27 publications

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“…While the benefits of physiotherapy after THA are generally acknowledged [ 1 ], and it frequently takes place in acute care clinics [ 17 , 18 ], there is a lack of consensus on the exact therapy program and only little evidence from controlled clinical trials, as a systematic review of the literature that appeared after 2008 [ 19 ] has shown. Other reviews and meta-analyses confirmed this view [ 19 , 20 , 21 ].…”

Section: Discussionmentioning

confidence: 99%

Mobile Robot-Based Gait Training after Total Hip Arthroplasty (THA) Improves Walking in Biomechanical Gait Analysis

Röhner

Mayfarth²,

Sternitzke³

et al. 2021

JCM

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There are multiple attempts to decrease costs in the healthcare system while maintaining a high treatment quality. Digital therapies receive increasing attention in clinical practice, mainly relating to home-based exercises supported by mobile devices, eventually in combination with wearable sensors. The aim of this study was to determine if patients following total hip arthroplasty (THA) could benefit from gait training on crutches conducted by a mobile robot in a clinical setting. Method: This clinical trial was conducted with 30 patients following total hip arthroplasty. Fifteen patients received the conventional physiotherapy program in the clinic (including 5 min of gait training supported by a physiotherapist). The intervention group of 15 patients passed the same standard physiotherapy program, but the 5-min gait training supported by a physiotherapist was replaced by 2 × 5 min of gait training conducted by the robot. Length of stay of the patients was set to five days. Biomechanical gait parameters of the patients were assessed pre-surgery and upon patient discharge. Results: While before surgery no significant difference in gait parameters was existent, patients from the intervention group showed a significant higher absolute walking speed (0.83 vs. 0.65 m/s, p = 0.029), higher relative walking speed (0.2 vs. 0.16 m/s, p = 0.043) or shorter relative cycle time (3.35 vs. 3.68 s, p = 0.041) than the patients from the control group. Conclusion: The significant higher walking speed of patients indicates that such robot-based gait training on crutches may shorten length of stay (LOS) in acute clinics. However, the number of patients involved was rather small, thus calling for further studies.

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Section: Discussionmentioning

confidence: 99%

Mobile Robot-Based Gait Training after Total Hip Arthroplasty (THA) Improves Walking in Biomechanical Gait Analysis

Röhner

Mayfarth²,

Sternitzke³

et al. 2021

JCM

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“…Regarding the follower robots, the ROGER project [ 20 ] developed a mobile Socially Assistive Robot (SAR) to support patients after surgery in hip endoprosthetics. ROGER is a robotic gait coach that can navigate in clinic hallways, accompanying and observing the self-training of patients.…”

Section: State Of the Artmentioning

confidence: 99%

ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments

Guffanti

Brunete

Hernando

et al. 2021

Sensors

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Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multiple medical applications and achieve new discoveries. This study proposes the use of a mobile robotic platform based on depth cameras to perform the analysis of human gait in practical scenarios. The aim is to prove the validity of this robot and its applicability in clinical settings. The mechanical and software design of the system is presented, as well as the design of the controllers of the lane-keeping, person-following, and servoing systems. The accuracy of the system for the evaluation of joint kinematics and the main gait descriptors was validated by comparison with a Vicon-certified system. Some tests were performed in practical scenarios, where the effectiveness of the lane-keeping algorithm was evaluated. Clinical tests with patients with multiple sclerosis gave an initial impression of the applicability of the instrument in patients with abnormal walking patterns. The results demonstrate that the system can perform gait analysis with high accuracy. In the curved sections of the paths, the knee joint is affected by occlusion and the deviation of the person in the camera reference system. This issue was greatly improved by adjusting the servoing system and the following distance. The control strategy of this robot was specifically designed for the analysis of human gait from the frontal part of the participant, which allows one to capture the gait properly and represents one of the major contributions of this study in clinical practice.

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“…There are also detections that do not have additional support from other modules, such as the leg detections. For Algorithm 1: Tracking cycle 1 for all tracking modules do 2 reset belief to begin of rewind interval; 3 for all detection timestamps t in rewind intervaldo 4 for all tracking modules do 5 predict belief using ∆t from previous detection; 6 while unprocessed detections at time t do 7 compute matrix A of all association probabilities to unprocessed detections at t; 8 find maximum element a h,d ∈ A; 9 update hypothesis h using detection d; end 10 for all tracking modules do 11 predict belief to current time; 12 return belief state of current time; those, no additional features are computed and tracked; thus, an association is only based on position. The binary association probabilities a m h,d of all modules m get multiplied in Bayesian manner:…”

Section: Multimodal Tracking Frameworkmentioning

confidence: 99%

“…The work presented here was part of the research project ROGER (RObot-assisted Gait training in orthopEdic Rehabilitiation) [7] in which we developed a rehabilitation robot assisting patients to recover their physiological gait after an orthopedic surgery. After the surgery, the patients were encouraged to perform self-training consisting of walking exercises in an aisle of the hospital.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Modal Person Perception Framework for Socially Interactive Mobile Service Robots

Müller

Wengefeld

Trinh

et al. 2020

Sensors

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In order to meet the increasing demands of mobile service robot applications, a dedicated perception module is an essential requirement for the interaction with users in real-world scenarios. In particular, multi sensor fusion and human re-identification are recognized as active research fronts. Through this paper we contribute to the topic and present a modular detection and tracking system that models position and additional properties of persons in the surroundings of a mobile robot. The proposed system introduces a probability-based data association method that besides the position can incorporate face and color-based appearance features in order to realize a re-identification of persons when tracking gets interrupted. The system combines the results of various state-of-the-art image-based detection systems for person recognition, person identification and attribute estimation. This allows a stable estimate of a mobile robot’s user, even in complex, cluttered environments with long-lasting occlusions. In our benchmark, we introduce a new measure for tracking consistency and show the improvements when face and appearance-based re-identification are combined. The tracking system was applied in a real world application with a mobile rehabilitation assistant robot in a public hospital. The estimated states of persons are used for the user-centered navigation behaviors, e.g., guiding or approaching a person, but also for realizing a socially acceptable navigation in public environments.

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May I Keep an Eye on Your Training? Gait Assessment Assisted by a Mobile Robot

Cited by 14 publications

References 27 publications

Mobile Robot-Based Gait Training after Total Hip Arthroplasty (THA) Improves Walking in Biomechanical Gait Analysis

Mobile Robot-Based Gait Training after Total Hip Arthroplasty (THA) Improves Walking in Biomechanical Gait Analysis

ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments

A Multi-Modal Person Perception Framework for Socially Interactive Mobile Service Robots

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