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      EquiMoves: A Wireless Networked Inertial Measurement System for Objective Examination of Horse Gait

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          Abstract

          In this paper, we describe and validate the EquiMoves system, which aims to support equine veterinarians in assessing lameness and gait performance in horses. The system works by capturing horse motion from up to eight synchronized wireless inertial measurement units. It can be used in various equine gait modes, and analyzes both upper-body and limb movements. The validation against an optical motion capture system is based on a Bland–Altman analysis that illustrates the agreement between the two systems. The sagittal kinematic results (protraction, retraction, and sagittal range of motion) show limits of agreement of ± 2.3 degrees and an absolute bias of 0.3 degrees in the worst case. The coronal kinematic results (adduction, abduction, and coronal range of motion) show limits of agreement of 8.8 and 8.1 degrees, and an absolute bias of 0.4 degrees in the worst case. The worse coronal kinematic results are most likely caused by the optical system setup (depth perception difficulty and suboptimal marker placement). The upper-body symmetry results show no significant bias in the agreement between the two systems; in most cases, the agreement is within ±5 mm. On a trial-level basis, the limits of agreement for withers and sacrum are within ±2 mm, meaning that the system can properly quantify motion asymmetry. Overall, the bias for all symmetry-related results is less than 1 mm, which is important for reproducibility and further comparison to other systems.

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          Lab and field experiments: are they the same animal?

          To advance our understanding of biological processes we often plan our experiments based on published data. This can be confusing though, as data from experiments performed in a laboratory environment are sometimes different from, or completely opposite to, findings from similar experiments performed in the "real world". In this mini-review, we discuss instances where results from laboratory experiments differ as a result of laboratory housing conditions, and where they differ from results gathered in the field environment. Experiments involving endocrinology and behavior appear to be particularly susceptible to influence from the environment in which they are performed. As such, we have attempted to promote discussion of the influence of housing environment on the reproductive axis, circadian biology and behavior, immune function, stress biology, neuroplasticity and photoperiodism. For example, why should a rodent species be diurnal in one housing environment yet nocturnal in another? Are data that are gathered from experiments in the laboratory applicable to the field environment, and vice-versa? We hope not only to highlight the need for experiments in both lab and field when looking at complex biological systems, but also to promote frank discussion of discordant data. Perhaps, just as study of individual variation has been gaining momentum in recent years, data from variation between experimental arenas can provide us with novel lines of research.
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            Interactive wearable systems for upper body rehabilitation: a systematic review

            Background The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This paper reviews related research with the aim: 1) To inventory and classify interactive wearable systems for movement and posture monitoring during upper body rehabilitation, regarding the sensing technology, system measurements and feedback conditions; 2) To gauge the wearability of the wearable systems; 3) To inventory the availability of clinical evidence supporting the effectiveness of related technologies. Method A systematic literature search was conducted in the following search engines: PubMed, ACM, Scopus and IEEE (January 2010–April 2016). Results Forty-five papers were included and discussed in a new cuboid taxonomy which consists of 3 dimensions: sensing technology, feedback modalities and system measurements. Wearable sensor systems were developed for persons in: 1) Neuro-rehabilitation: stroke (n = 21), spinal cord injury (n = 1), cerebral palsy (n = 2), Alzheimer (n = 1); 2) Musculoskeletal impairment: ligament rehabilitation (n = 1), arthritis (n = 1), frozen shoulder (n = 1), bones trauma (n = 1); 3) Others: chronic pulmonary obstructive disease (n = 1), chronic pain rehabilitation (n = 1) and other general rehabilitation (n = 14). Accelerometers and inertial measurement units (IMU) are the most frequently used technologies (84% of the papers). They are mostly used in multiple sensor configurations to measure upper limb kinematics and/or trunk posture. Sensors are placed mostly on the trunk, upper arm, the forearm, the wrist, and the finger. Typically sensors are attachable rather than embedded in wearable devices and garments; although studies that embed and integrate sensors are increasing in the last 4 years. 16 studies applied knowledge of result (KR) feedback, 14 studies applied knowledge of performance (KP) feedback and 15 studies applied both in various modalities. 16 studies have conducted their evaluation with patients and reported usability tests, while only three of them conducted clinical trials including one randomized clinical trial. Conclusions This review has shown that wearable systems are used mostly for the monitoring and provision of feedback on posture and upper extremity movements in stroke rehabilitation. The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and movement performance during upper body rehabilitation. Systems featuring sensors embedded in wearable appliances or garments are only beginning to emerge. Similarly, clinical evaluations are scarce and are further needed to provide evidence on effectiveness and pave the path towards implementation in clinical settings.
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              The Use of Wearable Microsensors to Quantify Sport-Specific Movements.

              Microtechnology has allowed sport scientists to understand the locomotor demands of various sports. While wearable global positioning technology has been used to quantify the locomotor demands of sporting activities, microsensors (i.e. accelerometers, gyroscopes and magnetometers) embedded within the units also have the capability to detect sport-specific movements.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                13 March 2018
                March 2018
                : 18
                : 3
                : 850
                Affiliations
                [1 ]Inertia Technology B.V., 7521 AG Enschede, The Netherlands; mihai@ 123456inertia-technology.com (M.M.-P.); raluca@ 123456inertia-technology.com (R.M.-P.); berendjan@ 123456inertia-technology.com (B.J.v.d.Z.)
                [2 ]Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, The Netherlands; F.M.SerraBraganca@ 123456uu.nl (F.S.B.); W.Back@ 123456uu.nl (W.B.); r.vanweeren@ 123456uu.nl (R.v.W.)
                [3 ]Rosmark Consultancy, 6733 AA Wekerom, The Netherlands; info@ 123456rosmark.nl
                [4 ]Department of Surgery and Anaesthesia of Domestic Animals, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium
                [5 ]Department of Computer Science, Pervasive Systems Group, University of Twente, 7522 NB Enschede, The Netherlands; p.j.m.havinga@ 123456utwente.nl
                Author notes
                [* ]Correspondence: stephan@ 123456inertia-technology.com ; Tel.: +31-53-711-3408
                Author information
                https://orcid.org/0000-0001-6814-9870
                https://orcid.org/0000-0001-8514-7949
                https://orcid.org/0000-0003-0884-5334
                https://orcid.org/0000-0002-6654-1817
                Article
                sensors-18-00850
                10.3390/s18030850
                5877382
                29534022
                07c6a1cf-82fc-459d-97ad-951f471f63f0
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 22 December 2017
                : 03 March 2018
                Categories
                Article

                Biomedical engineering
                horse,gait analysis,lameness,imu,optical motion capture,agreement analysis
                Biomedical engineering
                horse, gait analysis, lameness, imu, optical motion capture, agreement analysis

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