Gait analysis of patients with knee osteoarthritis by using elevation angle: confirmation of the planar law and analysis of angular difference in the approximate plane

Ishikawa, Yuki; An, Qi; Nakagawa, Junki; Oka, Hiroyuki; Yasui, Toshihiro; Tojima, Michio; Inokuchi, Haruhi; Haga, Nobuhiko; Yamakawa, Hiroshi; Tamura, Yusuke; Yamashita, Atsushi; Asama, Hajime

doi:10.1080/01691864.2016.1229217

Cited by 15 publications

(9 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A planar law applies to both walking and running, as well as to other gait modes ( Grasso et al, 2000 ; Ivanenko et al, 2007 ). It distinguishes between different developmental stages of human walk ( Cheron et al, 2001b ; Cheron et al, 2001a ; Ivanenko et al, 2004 ; Dominici et al, 2011 ), as well as between normal and pathological gait ( Grasso et al, 2004b ; Laroche et al, 2007 ; Leurs et al, 2012 ; Degelaen et al, 2013 ; Cappellini et al, 2016 ; Ishikawa et al, 2017 ; Wallard et al, 2018 ). Importantly, it has been shown that the planar covariation in humans is not a trivial consequence of the geometrical and kinematic relationships between different limb segments ( Ivanenko et al, 2008 ).…”

Section: Introductionmentioning

confidence: 99%

A kinematic synergy for terrestrial locomotion shared by mammals and birds

Catavitello

Ivanenko

Lacquaniti

2018

eLife

View full text Add to dashboard Cite

Locomotion of tetrapods on land adapted to different environments and needs resulting in a variety of different gait styles. However, comparative analyses reveal common principles of limb movement control. Here, we report that a kinematic synergy involving the planar covariation of limb segment motion holds in 54 different animal species (10 birds and 44 mammals), despite large differences in body size, mass (ranging from 30 g to 4 tonnes), limb configuration, and amplitude of movements. This kinematic synergy lies at the interface between the neural command signals output by locomotor pattern generators, the mechanics of the body center of mass and the external environment, and it may represent one neuromechanical principle conserved in evolution to save mechanical energy.

show abstract

Section: Introductionmentioning

confidence: 99%

A kinematic synergy for terrestrial locomotion shared by mammals and birds

Catavitello

Ivanenko

Lacquaniti

2018

eLife

View full text Add to dashboard Cite

show abstract

“…Such planar covariation of the elevation angles held for various gaits, such as running (Hicheur et al, 2006; Ivanenko et al, 2007), curved walking (Courtine and Schieppati, 2004), backward walking (Grasso et al, 1998; Hicheur et al, 2006), walking on inclined surfaces (Noble and Prentice, 2008), walking with bent or erect posture (Grasso et al, 2000), stepping over an obstacle (Ivanenko et al, 2005b; Maclellan and McFadyen, 2010), walking with body weight unloading (Ivanenko et al, 2002), and walking on a slippery surface (Cappellini et al, 2010), which suggests an invariant characteristic in locomotion. In addition, this characteristic appeared in toddlers (Cheron et al, 2001; Ivanenko et al, 2004, 2005a; Dominici et al, 2007, 2010; Hallemans and Aerts, 2009; Cappellini et al, 2016); neonates (Dominici et al, 2011); gait disorders (Grasso et al, 2004; Laroche et al, 2007; Leurs et al, 2012; Martino et al, 2014; Cappellini et al, 2016; Ishikawa et al, 2017; Wallard et al, 2018); and also various animals (Catavitello et al, 2018), including cats (Poppele and Bosco, 2003), dogs (Catavitello et al, 2015), monkeys (Courtine et al, 2005; Ogihara et al, 2012), and birds (Ogihara et al, 2014). Investigating the coordination structures has provided useful insights for adaptation mechanisms in locomotion.…”

Section: Discussionmentioning

confidence: 99%

Variant and Invariant Spatiotemporal Structures in Kinematic Coordination to Regulate Speed During Walking and Running

Oshima

Aoi

Funato

et al. 2019

Front. Comput. Neurosci.

View full text Add to dashboard Cite

Humans walk, run, and change their speed in accordance with circumstances. These gaits are rhythmic motions generated by multi-articulated movements, which have specific spatiotemporal patterns. The kinematic characteristics depend on the gait and speed. In this study, we focused on the kinematic coordination of locomotor behavior to clarify the underlying mechanism for the effect of speed on the spatiotemporal kinematic patterns for each gait. In particular, we used seven elevation angles for the whole-body motion and separated the measured data into different phases depending on the foot-contact condition, that is, single-stance phase, double-stance phase, and flight phase, which have different physical constraints during locomotion. We extracted the spatiotemporal kinematic coordination patterns with singular value decomposition and investigated the effect of speed on the coordination patterns. Our results showed that most of the whole-body motion could be explained by only two sets of temporal and spatial coordination patterns in each phase. Furthermore, the temporal coordination patterns were invariant for different speeds, while the spatial coordination patterns varied. These findings will improve our understanding of human adaptation mechanisms to tune locomotor behavior for changing speed.

show abstract

“…Fourth, conversion of sensor data in meaningful summary statistics may introduce specific biases in the musculoskeletal context. Studies have shown that algorithms that perform well in healthy volunteers, often do not perform well in people with musculoskeletal conditions, who tend to walk slower and have different gait characteristics [ 98 , 99 ].…”

Section: Main Textmentioning

confidence: 99%

Smartphones for musculoskeletal research – hype or hope? Lessons from a decennium of mHealth studies

Beukenhorst

Druce

Cock

2022

BMC Musculoskelet Disord

View full text Add to dashboard Cite

Background Smartphones provide opportunities for musculoskeletal research: they are integrated in participants’ daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. Body In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains. We critically appraised existing literature, debunking some myths around the advantages of smartphones: the myth that smartphone studies automatically enable high engagement, that they reach more representative samples, that they cost little, and that sensor data is objective. We provide a nuanced view of evidence in these areas and discuss strategies to increase engagement, to reach representative samples, to reduce costs and to avoid potential sources of subjectivity in analysing sensor data. Conclusion If smartphone studies are designed without awareness of the challenges inherent to smartphone use, they may fail or may provide biased results. Keeping participants of smartphone studies engaged longitudinally is a major challenge. Based on prior research, we provide 6 actions by researchers to increase engagement. Smartphone studies often have participants that are younger, have higher incomes and high digital literacy. We provide advice for reaching more representative participant groups, and for ensuring that study conclusions are not plagued by bias resulting from unrepresentative sampling. Costs associated with app development and testing, data storage and analysis, and tech support are substantial, even if studies use a ‘bring your own device’-policy. Exchange of information on costs, collective app development and usage of open-source tools would help the musculoskeletal community reduce costs of smartphone studies. In general, transparency and wider adoption of best practices would help bringing smartphone studies to the next level. Then, the community can focus on specific challenges of smartphones in musculoskeletal contexts, such as symptom-related barriers to using smartphones for research, validating algorithms in patient populations with reduced functional ability, digitising validated questionnaires, and methods to reliably quantify pain, quality of life and fatigue.

show abstract

Gait analysis of patients with knee osteoarthritis by using elevation angle: confirmation of the planar law and analysis of angular difference in the approximate plane

Cited by 15 publications

References 22 publications

A kinematic synergy for terrestrial locomotion shared by mammals and birds

A kinematic synergy for terrestrial locomotion shared by mammals and birds

Variant and Invariant Spatiotemporal Structures in Kinematic Coordination to Regulate Speed During Walking and Running

Smartphones for musculoskeletal research – hype or hope? Lessons from a decennium of mHealth studies

Contact Info

Product

Resources

About