Energy expenditure rate in level and uphill treadmill walking determined from empirical models and foot inertial sensing data

Sabatini, A.M.; Martelloni, C.; Scapellato, S.; Cavallo, Filippo

doi:10.1049/el:20040076

Cited by 8 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the stance phase, the velocity obtained through calculating is the velocity error, and the attitude misalignment angle can be calculated using Equation (17). Taking the velocity error and the attitude misalignment angle as the observation, the positioning error can be estimated and compensated through the Kalman filter.…”

Section: Improved Pedestrian Positioning Algorithm Based On Iaa Zuptmentioning

confidence: 99%

See 1 more Smart Citation

Research on the Heading Calibration for Foot-Mounted Inertial Pedestrian-Positioning System Based on Accelerometer Attitude

et al. 2019

View full text Add to dashboard Cite

Foot-mounted inertial pedestrian positioning (FIPP) plays an important role for facilitating pedestrian activities. It is suitable for indoor environment applications where global navigation satellite systems are unavailable such as during firefighting and military actions. However, the positioning error of FIPP can increase rapidly due to the measurement noise of the sensors. Zero Velocity Update (ZUPT) is an error correction method proposed to solve this accumulative error. However, the heading misalignment angle, which results in a continuous increase in the positioning error, cannot be estimated by ZUPT. In order to solve this problem, the improved ZUPT based on the Improved Attitude Algorithm (IAA) according to accelerometer measurements is proposed in this paper. When a pedestrian is in the stance phase, the horizontal attitude is estimated by using accelerometer measurements. According to the relationship between the heading misalignment angle and horizontal attitude, the heading misalignment angle is obtained by a series of mathematical derivations. By taking the velocity error and the attitude misalignment angle as observations, the heading misalignment angle and positioning error can be estimated and compensated for through the Kalman filter. Finally, we use MTI-G710 sensor manufactured by XSENS for the actual test and the experiment results show that the proposed method is effectively correct.

show abstract

Section: Improved Pedestrian Positioning Algorithm Based On Iaa Zuptmentioning

confidence: 99%

“…When the pedestrian is in a stance phase, the ZUPT is used to correct the positioning error. In ZUPT, the velocity error is taken as the observation to estimate the navigation error caused by inertial sensors measurement noise using the Kalman Filter [14][15][16][17]. However, the systematic error model established for ZUPT is imperfect.…”

Section: Introductionmentioning

confidence: 99%

Research on the Heading Calibration for Foot-Mounted Inertial Pedestrian-Positioning System Based on Accelerometer Attitude

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The error correction is based on the following principle: on a regular basis, the foot is stationary during the ordinary gait to reduce the positioning error growth of the system. In theory, a longer error correction time has better convergence of the optimal estimation, better error compensation effect and higher positioning accuracy [ 17 , 18 , 19 ]. However, the length of the error correction time is directly affected by the velocity of pedestrian movement.…”

Section: Introductionmentioning

confidence: 99%

Research on the Forward and Reverse Calculation Based on the Adaptive Zero-Velocity Interval Adjustment for the Foot-Mounted Inertial Pedestrian-Positioning System

Wang

Guo

Sun

et al. 2018

Sensors

View full text Add to dashboard Cite

Pedestrian-positioning technology based on the foot-mounted micro inertial measurement unit (MIMU) plays an important role in the field of indoor navigation and has received extensive attention in recent years. However, the positioning accuracy of the inertial-based pedestrian-positioning method is rapidly reduced because of the relatively low measurement accuracy of the measurement sensor. The zero-velocity update (ZUPT) is an error correction method which was proposed to solve the cumulative error because, on a regular basis, the foot is stationary during the ordinary gait; this is intended to reduce the position error growth of the system. However, the traditional ZUPT has poor performance because the time of foot touchdown is short when the pedestrians move faster, which decreases the positioning accuracy. Considering these problems, a forward and reverse calculation method based on the adaptive zero-velocity interval adjustment for the foot-mounted MIMU location method is proposed in this paper. To solve the inaccuracy of the zero-velocity interval detector during fast pedestrian movement where the contact time of the foot on the ground is short, an adaptive zero-velocity interval detection algorithm based on fuzzy logic reasoning is presented in this paper. In addition, to improve the effectiveness of the ZUPT algorithm, forward and reverse multiple solutions are presented. Finally, with the basic principles and derivation process of this method, the MTi-G710 produced by the XSENS company is used to complete the test. The experimental results verify the correctness and applicability of the proposed method.

show abstract

“…where v is the speed of walking and a is the percent grade (Sabatini et al 2004). We assume a constant slow rate of walking at 0.5 km/hour to accommodate searching (Rodda, personal communication, Lardner, personal communication).…”

mentioning

confidence: 99%

Spatial economic analysis of early detection and rapid response strategies for an invasive species

Kaiser

Burnett

2010

Resource and Energy Economics

View full text Add to dashboard Cite

Economic impacts from invasive species, conveyed as expected damages to assets from invasion and expected costs of successful prevention and/or removal, may vary significantly across spatially differentiated landscapes. We develop a spatial-dynamic model for optimal early detection and rapid response (EDRR) policies, commonly exploited in the management of potential invaders around the world, and apply it to the case of the Brown treesnake (Boiga irregularis) in Oahu, Hawaii. EDRR consists of search activities beyond the ports of entry, where search (and potentially removal) efforts are targeted toward areas where credible evidence suggests the presence of an invader. EDRR costs are a spatially dependent variable related to the ease or difficulty of searching an area, while damages are assumed to be a population dependent variable. A myopic strategy in which search only occurs when and where current expected net returns are positive is attractive to managers, and, we find, significantly lowers present value losses (by $270m over 30 years). We find further that in the tradeoff between search costs and damages avoided, early and aggressive measures that search some high priority areas beyond points of entry even when current costs of search exceed current damages can save the island more ($295m over 30 years). Extensive or non-targeted search is not advised however.

show abstract

Energy expenditure rate in level and uphill treadmill walking determined from empirical models and foot inertial sensing data

Cited by 8 publications

References 4 publications

Research on the Heading Calibration for Foot-Mounted Inertial Pedestrian-Positioning System Based on Accelerometer Attitude

Research on the Heading Calibration for Foot-Mounted Inertial Pedestrian-Positioning System Based on Accelerometer Attitude

Research on the Forward and Reverse Calculation Based on the Adaptive Zero-Velocity Interval Adjustment for the Foot-Mounted Inertial Pedestrian-Positioning System

Spatial economic analysis of early detection and rapid response strategies for an invasive species

Contact Info

Product

Resources

About