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
Robert W. Cox, Rodrigo E. Martinez, Russell T. Baker and Lindsay Warren
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
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
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
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
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
Steriani Elavsky, Lenka Knapova, Adam Klocek and David Smahel
cell phone, 47% of which are smartphones ( Pew Research Center, 2017 ). The trends are similar in Europe, where 82% use the Internet, including 57% of those in the 55–74 age group ( Eurostat, 2016 ). Cell phone ownership in Europe among older adults has been reported at 86% ( Eurostat, 2016 ). Although
Diane K. Ehlers, Jennifer Huberty, Matthew Buman, Steven Hooker, Michael Todd and Gert-Jan de Vreede
Commercially available mobile and Internet technologies present a promising opportunity to feasibly conduct ecological momentary assessment (EMA). The purpose of this study was to describe a novel EMA protocol administered on middle-aged women’s smartphones via text messaging and mobile Internet.
Women (N = 9; mean age = 46.2 ± 8.2 y) received 35 text message prompts to a mobile survey assessing activity, self-worth, and self-efficacy over 14 days. Prompts were scheduled and surveys were administered using commercial, Internet-based programs. Prompting was tailored to each woman’s daily wake/sleep schedule. Women concurrently wore a wrist-worn accelerometer. Feasibility was assessed via survey completion, accelerometer wear, participant feedback, and researcher notes.
Of 315 prompted surveys, 287 responses were valid (91.1%). Average completion time was 1.52 ± 1.03 minutes. One participant’s activity data were excluded due to accelerometer malfunction, resulting in complete data from 8 participants (n = 252 [80.0%] valid observations). Women reported the survey was easily and quickly read/completed. However, most thought the accelerometer was inconvenient.
High completion rates and perceived usability suggest capitalizing on widely available technology and tailoring prompting schedules may optimize EMA in middle-aged women. However, researchers may need to carefully select objective monitors to maintain data validity while limiting participant burden.
Andrew A. Flatt and Michael R. Esco
This study evaluated the 7-d mean and coefficient of variation (CV) of supine and standing ultrashort log-transformed root mean square of successive R-R intervals multiplied by 20 (lnRMSSDx20) obtained with a smartphone application (app) in response to varying weekly training load (TL). In addition, the authors aimed to determine if these values could be accurately assessed in as few as 5 or 3 d/wk.
Nine women from a college soccer team performed daily heart-rate-variability measures with an app in supine and standing positions over 3 wk of moderate, high, and low TL. The mean and CV over 7, 5, and 3 d were compared within and between weeks.
The 5- and 3-d measures within each week provided very good to nearly perfect intraclass correlations (ICCs .74–.99) with typical errors ranging from 0.64 to 5.65 when compared with the 7-d criteria. The 7, 5, and 3-d supine CV and the 7-day standing CV were moderately lower during the low-load than the high-load week (P .003–.045, effect sizes 0.86–0.92), with no significant changes occurring in the other measures.
This study supports the use of the mean and CV of lnRMSSD measured across at least 5 d for reflecting weekly values. The supine lnRMssDx20 CV as measured across 7, 5, and 3 d was the most sensitive marker to the changes in TL in the 3-wk period.
Kurusart Konharn, Wichai Eungpinichpong, Kluaymai Promdee, Paramaporn Sangpara, Settapong Nongharnpitak, Waradanai Malila and Jirachai Karawa
The suitability of smartphone applications (apps) currently used to track walking/running may differ depending on a person’s weight condition. This study aimed to examine the validity and reliability of apps for both normal-weight and overweight/obese young adults.
Thirty normal-weight (aged 21.7 ± 1.0 years, BMI 21.3 ± 1.9 kg/m2) and 30 overweight/ obese young adults (aged 21.0 ± 1.4 years, BMI 28.6 ± 3.7 kg/m2) wore a smartphone and pedometer on their right hip while walking/running at 3 different intensities on treadmills. Apps was randomly assigned to each individual for measuring average velocity, step count, distance, and energy expenditure (EE), and these measurements were then analyzed.
The apps were not accurate in counting most of the measured variables and data fell significantly lower in the parameters than those measured with standard-reference instruments in both light and moderate intensity activity among the normal-weight group. Among the overweight and obese group, the apps were not accurate in detecting velocity, distance, or EE during either light or vigorous intensities. The percentages of mean difference were 30.1% to 48.9%.
Apps may not have sufficient accuracy to monitor important physical parameters of human body movement. Apps need to be developed that can, in particular, respond differently based on a person’s weight status.