Clinical Indoor Running Gait Analysis May Not Approximate Outdoor Running Gait Based on Novel Drone Technology

2021 ◽  
pp. 194173812110509
Author(s):  
Lindsay Lafferty ◽  
John Wawrzyniak ◽  
Morgan Chambers ◽  
Todd Pagliarulo ◽  
Arthur Berg ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Treadmill Running ◽  
Initial Contact ◽  
Natural Environments ◽  
Video Capture ◽  
Poor Agreement ◽  
Level Of Evidence ◽  
Moderate Agreement ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments

Background: Traditional running gait analysis is limited to artificial environments, but whether treadmill running approximates overground running is debated. This study aimed to compare treadmill gait analysis using fixed video with outdoor gait analysis using drone video capture. Hypothesis: Measured kinematics would be similar between natural outdoor running and traditional treadmill gait analysis. Study Design: Crossover study. Level of Evidence: Level 2. Methods: The study population included cross-country, track and field, and recreational athletes with current running mileage of at least 15 km per week. Participants completed segments in indoor and outdoor environments. Indoor running was completed on a treadmill with static video capture, and outdoor segments were obtained via drone on an outdoor track. Three reviewers independently performed clinical gait analysis on footage for 32 runners using kinematic measurements with published acceptable intra- and interrater reliability. Results: Of the 8 kinematic variables measured, 2 were found to have moderate agreement indoor versus outdoor, while 6 had fair to poor agreement. Foot strike at initial contact and rearfoot position at midstance had moderate agreement indoor versus outdoor, with a kappa of 0.54 and 0.49, respectively. The remaining variables: tibial inclination at initial contact, knee flexion angle initial contact, forward trunk lean full gait cycle, knee center position midstance, knee separation midstance, and lateral pelvic drop at midstance were found to have fair to poor agreement, ranging from 0.21 to 0.36. Conclusion: This study suggests that kinematics may differ between natural outdoor running and traditional treadmill gait analysis. Clinical Relevance: Providing recommendations for altering gait based on treadmill gait analysis may prove to be harmful if treadmill analysis does not approximate natural running environments. Drone technology could provide advancement in clinical running recommendations by capturing runners in natural environments.

scholarly journals Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson’s Populations

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6476
Author(s):  
Yunus Celik ◽  
Sam Stuart ◽  
Wai Lok Woo ◽  
Alan Godfrey
Keyword(s):  
Gait Analysis ◽  
Inertial Sensors ◽  
Lower Back ◽  
Outdoor Environments ◽  
Outdoor Walking ◽  
Absolute Agreement ◽  
Walking Environment ◽  
Indoor And Outdoor Environments ◽  
The Impact ◽  
Indoor And Outdoor

Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson′s Disease, PD) and/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 × lower back and 1 × shin/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.

scholarly journals Counting Dense Leaves under Natural Environments via anImproved Deep-Learning-Based Object Detection Algorithm

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1003
Author(s):  
Shenglian Lu ◽  
Zhen Song ◽  
Wenkang Chen ◽  
Tingting Qian ◽  
Yingyu Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Natural Environments ◽  
Detection Algorithms ◽  
Art Object ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Key Indicators

The leaf is the organ that is crucial for photosynthesis and the production of nutrients in plants; as such, the number of leaves is one of the key indicators with which to describe the development and growth of a canopy. The irregular shape and distribution of the blades, as well as the effect of natural light, make the segmentation and detection process of the blades difficult. The inaccurate acquisition of plant phenotypic parameters may affect the subsequent judgment of crop growth status and crop yield. To address the challenge in counting dense and overlapped plant leaves under natural environments, we proposed an improved deep-learning-based object detection algorithm by merging a space-to-depth module, a Convolutional Block Attention Module (CBAM) and Atrous Spatial Pyramid Pooling (ASPP) into the network, and applying the smoothL1 function to improve the loss function of object prediction. We evaluated our method on images of five different plant species collected under indoor and outdoor environments. The experimental results demonstrated that our algorithm which counts dense leaves improved average detection accuracy of 85% to 96%. Our algorithm also showed better performance in both detection accuracy and time consumption compared to other state-of-the-art object detection algorithms.

scholarly journals Evidence-Based Landscape Architecture for Human Health and Well-Being

2020 ◽  
Vol 12 (4) ◽  
pp. 1360 ◽  
Author(s):  
Robert D. Brown ◽  
Robert C. Corry
Keyword(s):  
Human Health ◽  
Architectural Design ◽  
Landscape Architecture ◽  
Well Being ◽  
Evidence Based ◽  
Natural Environments ◽  
The People ◽  
Outdoor Environments ◽  
The Usa ◽  
Health And Well Being

More than 80% of the people in the USA and Canada live in cities. Urban development replaces natural environments with built environments resulting in limited access to outdoor environments which are critical to human health and well-being. In addition, many urban open spaces are unused because of poor design. This paper describes case studies where traditional landscape architectural design approaches would have compromised design success, while evidence-based landscape architecture (EBLA) resulted in a successful product. Examples range from school-yard design that provides safe levels of solar radiation for children, to neighborhood parks and sidewalks that encourage people to walk and enjoy nearby nature. Common characteristics for integrating EBLA into private, public, and academic landscape architecture practice are outlined along with a discussion of some of the opportunities and barriers to implementation.

Impacts of Different Winter Storage Conditions on the Physiology of Diutinus Honey Bees (Hymenoptera: Apidae)

2021 ◽  
Author(s):  
Brandon K Hopkins ◽  
Priyadarshini Chakrabarti ◽  
Hannah M Lucas ◽  
Ramesh R Sagili ◽  
Walter S Sheppard
Keyword(s):  
Honey Bees ◽  
The United States ◽  
Storage Conditions ◽  
Colony Losses ◽  
Bee Colony ◽  
Causative Factors ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Physiological Markers ◽  
Honey Bee Colony Losses

Abstract Global decline in insect pollinators, especially bees, have resulted in extensive research into understanding the various causative factors and formulating mitigative strategies. For commercial beekeepers in the United States, overwintering honey bee colony losses are significant, requiring tactics to overwinter bees in conditions designed to minimize such losses. This is especially important as overwintered honey bees are responsible for colony expansion each spring, and overwintered bees must survive in sufficient numbers to nurse the spring brood and forage until the new ‘replacement’ workers become fully functional. In this study, we examined the physiology of overwintered (diutinus) bees following various overwintering storage conditions. Important physiological markers, i.e., head proteins and abdominal lipid contents were higher in honey bees that overwintered in controlled indoor storage facilities, compared with bees held outdoors through the winter months. Our findings provide new insights into the physiology of honey bees overwintered in indoor and outdoor environments and have implications for improved beekeeping management.

scholarly journals A Hybrid Framework for Mitigating Heading Drift for a Wearable Pedestrian Navigation System through Adaptive Fusion of Inertial and Magnetic Measurements

2021 ◽  
Vol 11 (4) ◽  
pp. 1902
Author(s):  
Liqiang Zhang ◽  
Yu Liu ◽  
Jinglin Sun
Keyword(s):  
Magnetic Measurements ◽  
Inertial Sensor ◽  
Angular Rate ◽  
Human Motion ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
Hybrid Framework ◽  
Outdoor Environments ◽  
Adaptive Fusion ◽  
Indoor And Outdoor Environments

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift.

scholarly journals Health Effects and Exposure Assessment to Bioaerosols in Indoor and Outdoor Environments

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 359
Author(s):  
Ewa Brągoszewska
Keyword(s):  
Exposure Assessment ◽  
Health Effects ◽  
Special Issue ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

The Atmosphere Special Issue entitled “Health Effects and Exposure Assessment to Bioaerosols in Indoor and Outdoor Environments” comprises five original papers [...]

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