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Caterina Pesce, Ilaria Masci, Rosalba Marchetti, Giuseppe Vannozzi and Mirko Schmidt

: 22089478 doi:10.1249/MSS.0b013e31823fb254 10.1249/MSS.0b013e31823fb254 Grimpampi , E. , Masci , I. , Pesce , C. , & Vannozzi , G. ( 2016 ). Quantitative assessment of developmental levels in overarm throwing using wearable inertial sensor technology . Journal of Sports Sciences, 34 , 1759

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Tsuyoshi Saida, Masayuki Kawada, Daijiro Kuroki, Yuki Nakai, Takasuke Miyazaki, Ryoji Kiyama and Yasuhiro Tsuneyoshi

. , Brunton , L.R. , Wylde , V. , Gooberman-Hill , R. , Heyligers , I.C. , . . . Grimm , B. ( 2016 ). Assessment of physical function following total hip arthroplasty: Inertial sensor based gait analysis is supplementary to patient-reported outcome measures . Clinical Biomechanics, 32, 171

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Vincent Shieh, Ashwini Sansare, Minal Jain, Thomas Bulea, Martina Mancini and Cris Zampieri

eventually in clinical practice. Systems that combine wearable inertial sensors with the software to collect and automatically analyze various motor tasks may have particular use in clinical research and practice. One such system, which is commercially available, is the MobilityLab system (APDM, Inc

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Anna C. Severin, Brendan J. Burkett, Mark R. McKean, Aaron N. Wiegand and Mark G.L. Sayers

ethics approval. Instrumentation This study used six 100-Hz inertial sensors (Nanotrak; Catapult Sports, Docklands, Australia) to track trunk, pelvis, and lower limb kinematics. Inertial sensors are a validated tool for kinematic analyses ( Cuesta-Vargas, Galán-Mercant, & Williams, 2010 ; Steins, Dawes

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Hitoshi Koda, Yoshihiro Kai, Shin Murata, Hironori Osugi, Kunihiko Anami, Takahiko Fukumoto and Hidetaka Imagita

.D. ( 2013 ). Review of fall risk assessment in geriatric populations using inertial sensors . Journal of NeuroEngineering and Rehabilitation, 10 ( 1 ), 91 . PubMed ID: 23927446 doi:10.1186/1743-0003-10-91 10.1186/1743-0003-10-91 Incel , N.A. , Ceceli , E. , Durukan , P.B. , Erdem , H

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Alan K. Bourke, Espen A. F. Ihlen and Jorunn L. Helbostad

.gaitpost.2015.07.062 10.1016/j.gaitpost.2015.07.062 Bourke , A.K. , Ihlen , E.A. , Bergquist , R. , Wik , P.B. , Vereijken , B. , & Helbostad , J.L. ( 2017 ). A physical activity reference data-set recorded from older adults using body-worn inertial sensors and video technology—The ADAPT study data

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Anantha Narayanan, Farzanah Desai, Tom Stewart, Scott Duncan and Lisa Mackay

males and 3 females); Healthy population, age = 23.1 (1.7) y RunScribe™ inertial sensors (Scribe Labs, CA) 9; 3-axis accelerometer, 10 Hz; Left and right lateral ankle, left and right hip, left and right wrist, left and right upper arm, and spine (T10) Direct observation and images captured every 30 s

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Ivan A. Trujillo-Priego, Judy Zhou, Inge F. Werner, Weiyang Deng and Beth A. Smith

University of Southern California. A parent or legal guardian signed an informed consent form before their infant’s participation. Data of leg movement activity were collected in-home using inertial sensors (Opals, APDM Inc., Portland, OR, USA). Infants wore the sensors 7–13 hours per day for seven

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Nancy Getchell, Nadja Schott and Ali Brian

, Pesce , C. , Getchell , N. , & Cappozzo , A. ( 2013 ). Assessing locomotor skills development in childhood using wearable inertial sensor devices: the running paradigm . Gait and Posture, 37 ( 4 ), 570 – 574 . PubMed ID: 23067877 doi: 10.1016/j.gaitpost.2012.09.017 Masci , I. , Vannozzii