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Robert W. Cox, Rodrigo E. Martinez, Russell T. Baker and Lindsay Warren

goniometry, is performed in a similar manner to goniometry, but the inclinometer is aligned with the distal limb to measure motion. 2 , 4 , 5 The ease and availability of digital inclinometers, specifically those created as smartphone applications, have anecdotally increased the use of inclinometry for ROM

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Neng Wan, Ming Wen, Jessie X. Fan, O. Fahina Tavake-Pasi, Sara McCormick, Kirsten Elliott and Emily Nicolosi

population groups in the United States such as youth, white adults, and African American adults. 11 , 14 – 16 However, little attention has been paid to PIs despite their higher risk of PA-related health problems. In recent years, mobile technologies, especially smartphones, have emerged as a new and

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Merrill D. Funk, Cindy L. Salazar, Miriam Martinez, Jesus Gonzalez, Perla Leyva, David Bassett Jr. and Murat Karabulut

goals. Use of activity tracking devices has increased exponentially in recent years and the research analyzing the accuracy of these devices has followed ( Bort-Roig, Gilson, Puig-Ribera, Contreras, & Trost, 2014 ; Evenson, Goto, & Furberg, 2015 ). The number of Americans using smartphones reached 88

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Daniel J. Plews, Ben Scott, Marco Altini, Matt Wood, Andrew E. Kilding and Paul B. Laursen

wishing to use HRV in the field. Photoplethysmography (PPG) is a technological advancement that may allow HRV to be measured simply via a smartphone device. PPG is measured via reflection through the illumination of the skin using a light-emitting diode (LED; eg, the smartphone’s flash) and through

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Paul A. Ullucci, Frank Tudini and Matthew F. Moran

currently allow smartphone users to assess 3-dimensional movements in real time using various applications. This technology has been found to be both reliable and valid when measuring range of motion in multiple joints, including cardinal plane range of motion of the cervical spine. 9 , 10 There is, however

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Justin W.Y. Lee, Ming-Jing Cai, Patrick S.H. Yung and Kai-Ming Chan

-based test that requires minimal equipment and training to administer would be an ideal measurement tool. We have developed a simple and more accessible alternative testing method, named the Chinese University of Hong Kong (CUHK) Nordic break-point test, which utilizes a smartphone application to measure

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Mohammadreza Pourahmadi, Hamid Hesarikia, Ali Ghanjal and Alireza Shamsoddini

Smartphones have become central to our lives and provide users direct and instant access to a wealth of electronic media (ie, the Internet, e-mail, and instant messaging) and numerous applications (apps). The number of smartphone users has been increased exponentially with over 1.91 billion users

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Meaghan Nolan, J. Ross Mitchell and Patricia K. Doyle-Baker

Background:

The popularity of smartphones has led researchers to ask if they can replace traditional tools for assessing free-living physical activity. Our purpose was to establish proof-of-concept that a smartphone could record acceleration during physical activity, and those data could be modeled to predict activity type (walking or running), speed (km·h−1), and energy expenditure (METs).

Methods:

An application to record and e-mail accelerations was developed for the Apple iPhone®/iPod Touch®. Twentyfive healthy adults performed treadmill walking (4.0 km·h−1 to 7.2 km·h1) and running (8.1 km·h−1 to 11.3 km·h−1) wearing the device. Criterion energy expenditure measurements were collected via metabolic cart.

Results:

Activity type was classified with 99% accuracy. Speed was predicted with a bias of 0.02 km·h−1 (SEE: 0.57 km·h−1) for walking, –0.03 km·h−1 (SEE: 1.02 km·h−1) for running. Energy expenditure was predicted with a bias of 0.35 METs (SEE: 0.75 METs) for walking, –0.43 METs (SEE: 1.24 METs) for running.

Conclusion:

Our results suggest that an iPhone/iPod Touch can predict aspects of locomotion with accuracy similar to other accelerometer-based tools. Future studies may leverage this and the additional features of smartphones to improve data collection and compliance.

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Sun J. Kang, Jae-Pil Ha and Marion E. Hambrick

The popularity of smartphones has led to the creation of sport-related mobile applications in the areas of games, fitness, information, and events for sport consumers. The main purpose of this study was to examine why college students use sport-related mobile applications and what benefits they received from their usage. The study employed the Motivation Scale for Sport Online Consumption and the Technology Acceptance Model to understand this usage in more detail. Using a mixed-method approach, the study revealed that college students identified fanship, convenience, and information as primary motives for using their sport-related mobile applications. For college students who are sport fans, supporting their fanship through these applications represents an important aspect of their lifestyle. Sport managers and sport application developers will benefit from understanding users’ intentions and motives as the market for sport-related applications continues to grow.

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Robert H. Wellmon, Dawn T. Gulick, Mark L. Paterson and Colleen N. Gulick

Context:

Smartphones are being used in a variety of practice settings to measure joint range of motion (ROM). A number of factors can affect the validity of the measurements generated. However, there are no studies examining smartphone-based goniometer applications focusing on measurement variability and error arising from the electromechanical properties of the device being used.

Objective:

To examine the concurrent validity and interrater reliability of 2 goniometric mobile applications (Goniometer Records, Goniometer Pro), an inclinometer, and a universal goniometer (UG).

Design:

Nonexperimental, descriptive validation study.

Setting:

University laboratory.

Participants:

3 physical therapists having an average of 25 y of experience.

Main Outcome Measures:

Three standardized angles (acute, right, obtuse) were constructed to replicate the movement of a hinge joint in the human body. Angular changes were measured and compared across 3 raters who used 3 different devices (UG, inclinometer, and 2 goniometric apps installed on 3 different smartphones: Apple iPhone 5, LG Android, and Samsung SIII Android). Intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to examine interrater reliability and concurrent validity.

Results:

Interrater reliability for each of the smartphone apps, inclinometer and UG were excellent (ICC = .995–1.000). Concurrent validity was also good (ICC = .998–.999). Based on the Bland-Altman plots, the means of the differences between the devices were low (range = –0.4° to 1.2°).

Conclusions:

This study identifies the error inherent in measurement that is independent of patient factors and due to the smartphone, the installed apps, and examiner skill. Less than 2° of measurement variability was attributable to those factors alone. The data suggest that 3 smartphones with the 2 installed apps are a viable substitute for using a UG or an inclinometer when measuring angular changes that typically occur when examining ROM and demonstrate the capacity of multiple examiners to accurately use smartphone-based goniometers.