Change search
Refine search result
1 - 4 of 4
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Arvidsson, Daniel
    et al.
    University of Gothenburg.
    Fridolfsson, Jonatan
    University of Gothenburg.
    Börjesson, Mats
    University of Gothenburg.
    Andersen, Lars Bo
    Western Norway University of Applied Sciences, Campus Sogndal, Norway..
    Ekblom, Örjan
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences, Åstrand Laboratory of Work Physiology.
    Dencker, Magnus
    Lund University.
    Brønd, Jan Christian
    University of Southern Denmark, Odense, Denmark.
    Re-examination of accelerometer data processing and calibration for the assessment of physical activity intensity.2019In: Scandinavian Journal of Medicine and Science in Sports, ISSN 0905-7188, E-ISSN 1600-0838, Vol. 29, no 10, p. 1442-1452Article in journal (Refereed)
    Abstract [en]

    This review reexamines use of accelerometer and oxygen uptake data for assessment of activity intensity. Accelerometers capture mechanical work, while oxygen uptake captures the energy cost of this work. Frequency filtering needs to be considered when processing acceleration data. A too restrictive filter attenuates the acceleration signal for walking and, to a higher degree, for running. This measurement error affects shorter (children) more than taller (adults) individuals due to their higher movement frequency. Less restrictive filtering includes more movement related signals and provide measures that better capture mechanical work, but may include more noise. An optimal filter cut-point is determined where most relevant acceleration signals are included. Further, accelerometer placement affects what part of mechanical work being captured. While the waist placement captures total mechanical work and therefore contributes to measures of activity intensity equivalent by age and stature, the thigh and wrist placements capture more internal work and do not provide equivalent measures. Value calibration of accelerometer measures is usually performed using measured oxygen uptake with the metabolic equivalent of task (MET) as reference measure of activity intensity. However, the use of MET is not stringent and is not a measure of activity intensity equivalent by age and stature. A candidate measure is the mass-specific net oxygen uptake, VO2 net (VO2 tot - VO2 stand). To improve measurement of physical activity intensity using accelerometers, research developments are suggested concerning processing of accelerometer data, use of energy expenditure as reference for activity intensity, and calibration procedure with absolute versus relative intensity. This article is protected by copyright. All rights reserved.

  • 2.
    Fridolfsson, Jonatan
    et al.
    University of Gothenburg.
    Börjesson, Mats
    University of Gothenburg.
    Buck, Christoph
    Leibniz Institute for Prevention Research and epidemiology (BIPS), Bremen, Germany.
    Ekblom, Örjan
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences, Åstrand Laboratory of Work Physiology.
    Ekblom Bak, Elin
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences, Åstrand Laboratory of Work Physiology.
    Hunsberger, Monica
    University of Gothenburg.
    Lissner, Lauren
    University of Gothenburg.
    Arvidsson, Daniel
    University of Gothenburg.
    Effects of Frequency Filtering on Intensity and Noise in Accelerometer-Based Physical Activity Measurements.2019In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 9, article id E2186Article in journal (Refereed)
    Abstract [en]

    In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect of wider frequency filters on measurements of PA, sedentary behavior (SED), and capturing of noise. Apart from the standard AG band-pass filter (0.29-1.63 Hz), modified filters with low-pass component cutoffs at 4 Hz, 10 Hz, or removed were analyzed. Calibrations against energy expenditure were performed with lab data from children and adults to generate filter-specific intensity cut-points. Free-living accelerometer data from children and adults were processed using the different filters and intensity cut-points. There was a contribution of acceleration related to PA at frequencies up to 10 Hz. The contribution was more pronounced at moderate and vigorous PA levels, although additional acceleration also occurred at SED. The classification discrepancy between AG and the wider filters was small at SED (1-2%) but very large at the highest intensities (>90%). The present study suggests an optimal low-pass frequency filter with a cutoff at 10 Hz to include all acceleration relevant to PA with minimal effect of noise.

  • 3. Maiwald, Christian
    et al.
    Arndt, Anton
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences, Laboratory for Biomechanics and Motor Control.
    Nester, Chris
    Jones, Richard
    Lundberg, Arne
    Wolf, Peter
    The effect of intracortical bone pin application on kinetics and tibiocalcaneal kinematics of walking gait2017In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 52, p. 129-134Article in journal (Refereed)
    Abstract [en]
    • Gait analysis using bone anchored markers requires local anaesthesia, which may affect subjects gait patterns.
    • Kinetic and kinematic variables were collected using two protocols (skin vs. bone anchored markers).
    • No systematic differences were found between the two protocols.
    • We conclude that the validity of the recorded variables is not affected by local anaesthesia.

    Bone anchored markers using intracortical bone pins are one of the few available methods for analyzing skeletal motion during human gait in-vivo without errors induced by soft tissue artifacts. However, bone anchored markers require local anesthesia and may alter the motor control and motor output during gait. The purpose of this study was to examine the effect of local anesthesia and the use of bone anchored markers on typical gait analysis variables. Five subjects were analyzed in two different gait analysis sessions. In the first session, a protocol with skin markers was used. In the second session, bone anchored markers were added after local anesthesia was applied. For both sessions, three dimensional infrared kinematics of the calcaneus and tibia segments, ground reaction forces, and plantar pressure data were collected. 95% confidence intervals and boxplots were used to compare protocols and assess the data distribution and data variability for each subject. Although considerable variation was found between subjects, within-subject comparison of the two protocols revealed non-systematic effects on the target variables. Two of the five subjects walked at reduced gait speed during the bone pin session, which explained the between-session differences found in kinetic and kinematic variables. The remaining three subjects did not systematically alter their gait pattern between the two sessions. Results support the hypothesis that local anesthesia and the presence of bone pins still allow a valid gait pattern to be analyzed.

  • 4.
    Zhou, Guang-Quan
    et al.
    Southeast University, Nanjing, China.
    Zhang, Yi
    Southeast University, Nanjing, China.
    Wang, Ruo-Li
    Karolinska Institute & Royal Institute of Technology, Stockholm.
    Zhou, Ping
    Southeast University, Nanjing, China.
    Zheng, Yong-Ping
    The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
    Tarassova, Olga
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences, Laboratory for Biomechanics and Motor Control.
    Arndt, Anton
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences, Laboratory for Biomechanics and Motor Control. Karolinska Institute.
    Chen, Qiang
    Southeast University, Nanjing, China.
    Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation.2018In: BioMed Research International, ISSN 2314-6133, E-ISSN 2314-6141, article id 3697835Article in journal (Refereed)
    Abstract [en]

    Displacement of the myotendinous junction (MTJ) obtained by ultrasound imaging is crucial to quantify the interactive length changes of muscles and tendons for understanding the mechanics and pathological conditions of the muscle-tendon unit during motion. However, the lack of a reliable automatic measurement method restricts its application in human motion analysis. This paper presents an automated measurement of MTJ displacement using prior knowledge on tendinous tissues and MTJ, precluding the influence of nontendinous components on the estimation of MTJ displacement. It is based on the perception of tendinous features from musculoskeletal ultrasound images using Radon transform and thresholding methods, with information about the symmetric measures obtained from phase congruency. The displacement of MTJ is achieved by tracking manually marked points on tendinous tissues with the Lucas-Kanade optical flow algorithm applied over the segmented MTJ region. The performance of this method was evaluated on ultrasound images of the gastrocnemius obtained from 10 healthy subjects (26.0±2.9 years of age). Waveform similarity between the manual and automatic measurements was assessed by calculating the overall similarity with the coefficient of multiple correlation (CMC).<italic> In vivo</italic> experiments demonstrated that MTJ tracking with the proposed method (CMC = 0.97±0.02) was more consistent with the manual measurements than existing optical flow tracking methods (CMC = 0.79±0.11). This study demonstrated that the proposed method was robust to the interference of nontendinous components, resulting in a more reliable measurement of MTJ displacement, which may facilitate further research and applications related to the architectural change of muscles and tendons. [ABSTRACT FROM AUTHOR]

1 - 4 of 4
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf