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ATLETİK PERFORMANS ÖLÇÜMÜNDE VE TAKİBİNDE KULLANILAN MOBİL UYGULAMALAR: GELENEKSEL BİR DERLEME

Yıl 2022, Cilt: 16 Sayı: 1, 1 - 21, 16.03.2022

Öz

Akıllı telefonların ve mobil cihazların insan yaşamının her alanında yaygın bir hale gelmesi bu cihazlarda çalışan yazılımların da geliştirilmesi talebini beraberinde getirmiştir. Mobil uygulamalar telefon, tablet veya saat gibi mobil cihazlarda çalışmak üzere tasarlanmış yazılım uygulamalarıdır. Mobil cihazlar için özel olarak kodlanmış ve tasarlanmış olan bu yazılımlar teknolojinin de gelişimi ile beraber son 20 yılda bireylerin hayatında vazgeçilmez bir yer almıştır. Mobil uygulamaların genellikle oyun, hava durumu, iletişim, haritalar ve navigasyon, müzik, spor ve haber alma kategorileri üzerine kullanıldığı belirtilmektedir. Spor kategorisi altındaki mobil uygulamaların önemli bir kısmı sağlık ve egzersiz bilimlerinde veri toplamak ve performansı takip etmek amacıyla kullanılmaktadır. Performans ölçümünde ve takibinde kullanılan mobil uygulamaların sayısı ticari olarak erişilebilir olmalarından dolayı da gün geçtikçe artmaktadır. Performans ölçümünde ve takibinde kullanılan mobil uygulamalara karşı artan bu ilgi ve yönelim, bu uygulamalarda kullanılan terimlerin, ekipmanların, metotların ve uygulama aşamalarının doğru anlaşılması gerekliliğini ortaya çıkarmaktadır. Dolayısıyla bu derlemenin amacı, araştırmacılar ve uygulayıcılar tarafından sportif performans alanında kullanımı gün geçtikçe artan mobil uygulamaları bütünsel bir bakış açısıyla tanımlamak, bilimsel araştırmalar doğrultusunda incelemek, kullanımındaki terimleri ve ekipmanları açıklamak ve uygulama basamakları hakkında bilgi vermektir.

Destekleyen Kurum

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Proje Numarası

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Teşekkür

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Kaynakça

  • Kaur A., Kaur K. (2018). Systematic literature review of mobile application development and testing effort estimation. Journal of King Saud University. Computer and Information Sciences. 34(2), 1-15.
  • Buse U., Şeyda G., Tamer E., Özcan E. (2020). Mobil uygulama seçiminde etkili olan kriterlerin belirlenmesi ve örnek uygulama. İstanbul İktisat Dergisi. 70(1), 113-139.
  • Aitken M., Clancy B., Nass D. (2017). The growing value of digital health: evidence and impact on human health and the healthcare system. IQVIA Institute for Human Data Science.
  • Yıldırır SC., Kaplan B. (2019) mobil uygulama kullanımının benimsenmesi: teknoloji kabul modeli ile bir çalışma. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 10(19), 22-51.
  • Islam R., Islam R., Mazumder T. (2010). Mobile application and its global impact. International Journal of Engineering & Technology. 10(6), 72-78.
  • Peart DJ., Balsalobre-Fernández C., Shaw MP. (2019). Use of mobile applications to collect data in sport, health, and exercise science: A narrative review. The Journal of Strength & Conditioning Research. 33(4), 1167-1177.
  • Thompson WR. (2016). Worldwide survey of fitness trends for 2017. ACSM's Health & Fitness Journal. 20(6), 8-17.
  • Bromilow L., Stanton R., Humphries B. (2020). A structured e-investigation into the prevalence and acceptance of smartphone applications by exercise professionals. The Journal of Strength & Conditioning Research. 34(5), 1330-1339.
  • Muntaner-Mas A., Martinez-Nicolas A., Lavie CJ., Blair SN., Ross R., Arena R., Ortega FB. (2019). A systematic review of fitness apps and their potential clinical and sports utility for objective and remote assessment of cardiorespiratory fitness. Sports Medicine. 49(4), 587-600.
  • Modave F., Bian J., Leavitt T., Bromwell J., Harris C., Vincent H. (2015). Low quality of free coaching apps with respect to the American College of Sports Medicine Guidelines: A review of current mobile apps. Journal of Medical Internet Research. 3(3), e77.
  • Achten J., Jeukendrup AE. (2003). Heart rate monitoring. Sports Medicine 33, 517-538.
  • Allen J. (2007) Photoplethysmography and its application in clinical physiological measurement. Physiological measurement. 28(3), 1-39
  • Popescu AL., Ionescu RT., Popescu D. (2016). Cardiowatch: A solution for monitoring the heart rate on a Mobile device. University Politehnica of Bucharest Scientific Bulletin Series C-electrical Engineering and Computer Science. 78(3), 63-74.
  • Pelegris P., Banitsas K., Orbach T., Marias K. (2010). A novel method to detect heart beat rate using a mobile phone. A Novel Method to Detect Heart Beat Rate Using a Mobile Phone. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 5488-5491, Buenos Aires, Arjantin.
  • Coppetti T., Brauchlin A., Müggler S., Attinger-Toller A., Templin C., Schönrath F., Wyss CA. (2017). Accuracy of smartphone apps for heart rate measurement. European Journal of Preventive Cardiology. 24(12), 1287-1293.
  • De Ridder B., Van Rompaey B., Kampen JK., Haine S., Dilles T. (2018). Smartphone apps using photoplethysmography for heart rate monitoring: meta-analysis. Journal of Medical Internet Research. 2(1), e8802.
  • Almeida M., Bottino A., Ramos P., Araujo CG. (2019). Measuring heart rate during exercise: from artery palpation to monitors and apps. International Journal of Cardiovascular Sciences. 32(4), 396-407.
  • Chen YS., Clemente FM., Bezerra P., Lu YX. (2020). Ultra-short-term and short-term heart rate variability recording during training camps and an international tournament in U-20 national futsal players. International Journal of Environmental Research and Public Health. 17(3), 775.
  • Li KHC., White FA., Tipoe T., Liu T., Wong MC., Jesuthasan A., Yan BP. (2019). The current state of mobile phone apps for monitoring heart rate, heart rate variability, and atrial fibrillation: narrative review. Journal of Medical Internet Research. 7(2), e11606.
  • Javaloyes A., Sarabia JM., Lamberts RP., Moya-Ramon M. (2019). Training prescription guided by heart-rate variability in cycling. International Journal of Sports Physiology and Performance. 14(1), 23-32.
  • Earnest CP., Jurca R., Church T., Chicharro JL., Hoyos J., Lucia A. (2004). Relation between physical exertion and heart rate variability characteristics in professional cyclists during the Tour of Spain. British Journal of Sports Medicine. 38(5), 568-575.
  • Pichot V., Roche F., Gaspoz JM., Enjolras F., Antoniadis A., Minini P., Barthelemy JC. (2000). Relation between heart rate variability and training load in middle-distance runners. Medicine and Science in Sports and Exercise. 32(10), 1729-1736.
  • Perrotta AS., Jeklin AT., Hives BA., Meanwell LE. Warburton DE. (2017). Validity of the elite HRV smartphone application for examining heart rate variability in a field-based setting. The Journal of Strength & Conditioning Research. 31(8), 2296-2302.
  • Bolkhovsky JB., Scully CG., Chon KH. (2012). Statistical analysis of heart rate and heart rate variability monitoring through the use of smart phone cameras. 1610-1613. 34th Annual International Conference of the IEEE EMBS. San Diego. California. USA.
  • Deelen I., Janssen M., Vos S., Kamphuis CBM., Ettema D. (2019). Attractive running environments for all? A cross-sectional study on physical environmental characteristics and runners' motives and attitudes, in relation to the experience of the running environment. Public Health. 19(1), 1-15.
  • Borgers J., Vanreusel B., Vos S., Forsberg P., Scheerder J. (2016). Do light sport facilities foster sports participation? A case study on the use of bark running tracks. International Journal of Sport Policy and Politics. 8(2), 287-304.
  • Hallmann K., Wicker P. (2012). Consumer profiles of runners at marathon races. International Journal of Event and Festival Management. 3(2), 171-187.
  • Scheerder J., Breedveld K., Borgers J. (2015). Running across Europe: the rise and size of one of the largest sport markets. 1. Edition. Palgrave Macmillan. New York (US), 1-3.
  • Shipway R., Holloway I. (2016). Health and the running body: Notes from an ethnography. International Review for the Sociology of Sport. 51(1), 78-96.
  • Vos S., Janssen M., Goudsmit J., Lauwerijssen C., Brombacher A. (2016). From problem to solution: Developing a personalized smartphone application for recreational runners following a three-step design approach. Procedia Engineering. 147, 799-805.
  • Vickey T., Breslin J., Williams A. (2013). Fitness-There's an App for That: Review of Mobile Fitness Apps. International Journal of Sport & Society 3(4), 1-20.
  • Keogh JW., Cox A., Anderson S., Liew B., Olsen A., Schram B., Furness, J. (2019). Reliability and validity of clinically accessible smartphone applications to measure joint range of motion: A systematic review. PloS One. 14(5), e0215806.
  • Keogh JW., Espinosa HG., Grigg J. (2016). Evolution of smart devices and human movement apps: recommendations for use in sports science education and practice. Journal of Fitness Research. 5(Special), 14-15.
  • Pourahmadi MR., Ebrahimi TI., Sarrafzadeh J., Bahramian M., Mohseni‐Bandpei MA., Rajabzadeh F., Taghipour M. (2017). Reliability and concurrent validity of a new iPhone goniometric application for measuring active wrist range of motion: a cross‐sectional study in asymptomatic subjects. Journal of Anatomy. 230(3), 484-495.
  • Mann JB., Thyfault JP., Ivey PA., Sayers SP. (2010). The effect of autoregulatory progressive resistance exercise vs. linear periodization on strength improvement in college athletes. The Journal of Strength & Conditioning Research. 24(7), 1718-1723.
  • Mann JB., Ivey PA., Sayers SP. (2015). Velocity-based training in football. Strength & Conditioning Journal. 37(6), 52-57.
  • Robertson RJ., Goss FL., Aaron DJ., Gairola A., Kowallis RA., Liu Y., White B. (2008). One repetition maximum prediction models for children using the OMNI RPE scale. The Journal of Strength & Conditioning Research. 22(1), 196-201.
  • Fry AC., Kraemer WJ. (1997). Resistance exercise overtraining and overreaching. Sports Medicine. 23(2), 106-129.
  • Loturco I., Ugrinowitsch C., Tricoli V., Pivetti B., Roschel H. (2013). Different loading schemes in power training during the preseason promote similar performance improvements in Brazilian elite soccer players. The Journal of Strength & Conditioning Research. 27(7), 1791-1797.
  • Kravitz L., Akalan C., Nowicki K., Kinzey SJ. (2003). Prediction of 1 repetition maximum in high-school power lifters. The Journal of Strength & Conditioning Research. 17(1), 167-172.
  • González-Badillo JJ., Sánchez-Medina L. (2010). Movement velocity as a measure of loading intensity in resistance training. International Journal of Sports Medicine. 31(5), 347-352.
  • Jidovtseff B., Harris NK., Crielaard JM., Cronin JB. (2011). Using the load-velocity relationship for 1RM prediction. The Journal of Strength & Conditioning Research. 25(1), 267-270.
  • Balsalobre-Fernández C., Marchante D., Muñoz-López M., Jiménez SL. (2018). Validity and reliability of a novel iPhone app for the measurement of barbell velocity and 1RM on the bench-press exercise. Journal of Sports Sciences. 36(1), 64-70.
  • Balsalobre-Fernández C., Marchante D., Baz-Valle E., Alonso-Molero, I., Jiménez SL., Muñóz-López M. (2017). Analysis of wearable and smartphone-based technologies for the measurement of barbell velocity in different resistance training exercises. Frontiers in Physiology, 649.
  • Cetin O., Isik O. (2021). Validity and reliability of mylift app in determining 1-rm for deadlift and back squat exercises. European Journal of Human Movement. 46, 28-36.
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  • Pérez-Castilla A., Boullosa D., García-Ramos A. (2021). Reliability and validity of the iLOAD application for monitoring the mean set velocity during the back squat and bench press exercises performed against different loads. The Journal of Strength & Conditioning Research. 35, 57-65.
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MOBILE APPLICATIONS USED IN MEASUREMENT AND MONITORING OF ATHLETIC PERFORMANCE: A TRADITIONAL REVIEW

Yıl 2022, Cilt: 16 Sayı: 1, 1 - 21, 16.03.2022

Öz

The widespread use of smartphones and mobile devices in all areas of human life has led to the demand for the development of software running on these devices. Mobile apps are software applications designed to run on mobile devices such as phones, tablets, or watches. The softwares, coded and designed for mobile devices, have taken an indispensable place in the lives of individuals in the last 20 years with the development of technology. It is stated that mobile applications are generally used in the categories of games, weather, communication, maps and navigation, music, sports, and news. An important part of mobile applications under the category of sports is used to collect data and monitor performance in health and exercise sciences. The number of mobile applications used in performance measurement and monitoring is increasing day by day due to their commercial availability. This increasing interest and orientation towards mobile applications used in performance measurement and monitoring reveal the necessity of a correct understanding of the terms, equipment, methods, and application stages used in these applications. Therefore, the purpose of this review is to define mobile applications, which are increasingly used by researchers and practitioners in the field of sportive performance, from a holistic perspective, to examine them in line with scientific research, to explain the terms and equipment in their use, and to give information about the application steps.

Proje Numarası

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Kaynakça

  • Kaur A., Kaur K. (2018). Systematic literature review of mobile application development and testing effort estimation. Journal of King Saud University. Computer and Information Sciences. 34(2), 1-15.
  • Buse U., Şeyda G., Tamer E., Özcan E. (2020). Mobil uygulama seçiminde etkili olan kriterlerin belirlenmesi ve örnek uygulama. İstanbul İktisat Dergisi. 70(1), 113-139.
  • Aitken M., Clancy B., Nass D. (2017). The growing value of digital health: evidence and impact on human health and the healthcare system. IQVIA Institute for Human Data Science.
  • Yıldırır SC., Kaplan B. (2019) mobil uygulama kullanımının benimsenmesi: teknoloji kabul modeli ile bir çalışma. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 10(19), 22-51.
  • Islam R., Islam R., Mazumder T. (2010). Mobile application and its global impact. International Journal of Engineering & Technology. 10(6), 72-78.
  • Peart DJ., Balsalobre-Fernández C., Shaw MP. (2019). Use of mobile applications to collect data in sport, health, and exercise science: A narrative review. The Journal of Strength & Conditioning Research. 33(4), 1167-1177.
  • Thompson WR. (2016). Worldwide survey of fitness trends for 2017. ACSM's Health & Fitness Journal. 20(6), 8-17.
  • Bromilow L., Stanton R., Humphries B. (2020). A structured e-investigation into the prevalence and acceptance of smartphone applications by exercise professionals. The Journal of Strength & Conditioning Research. 34(5), 1330-1339.
  • Muntaner-Mas A., Martinez-Nicolas A., Lavie CJ., Blair SN., Ross R., Arena R., Ortega FB. (2019). A systematic review of fitness apps and their potential clinical and sports utility for objective and remote assessment of cardiorespiratory fitness. Sports Medicine. 49(4), 587-600.
  • Modave F., Bian J., Leavitt T., Bromwell J., Harris C., Vincent H. (2015). Low quality of free coaching apps with respect to the American College of Sports Medicine Guidelines: A review of current mobile apps. Journal of Medical Internet Research. 3(3), e77.
  • Achten J., Jeukendrup AE. (2003). Heart rate monitoring. Sports Medicine 33, 517-538.
  • Allen J. (2007) Photoplethysmography and its application in clinical physiological measurement. Physiological measurement. 28(3), 1-39
  • Popescu AL., Ionescu RT., Popescu D. (2016). Cardiowatch: A solution for monitoring the heart rate on a Mobile device. University Politehnica of Bucharest Scientific Bulletin Series C-electrical Engineering and Computer Science. 78(3), 63-74.
  • Pelegris P., Banitsas K., Orbach T., Marias K. (2010). A novel method to detect heart beat rate using a mobile phone. A Novel Method to Detect Heart Beat Rate Using a Mobile Phone. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 5488-5491, Buenos Aires, Arjantin.
  • Coppetti T., Brauchlin A., Müggler S., Attinger-Toller A., Templin C., Schönrath F., Wyss CA. (2017). Accuracy of smartphone apps for heart rate measurement. European Journal of Preventive Cardiology. 24(12), 1287-1293.
  • De Ridder B., Van Rompaey B., Kampen JK., Haine S., Dilles T. (2018). Smartphone apps using photoplethysmography for heart rate monitoring: meta-analysis. Journal of Medical Internet Research. 2(1), e8802.
  • Almeida M., Bottino A., Ramos P., Araujo CG. (2019). Measuring heart rate during exercise: from artery palpation to monitors and apps. International Journal of Cardiovascular Sciences. 32(4), 396-407.
  • Chen YS., Clemente FM., Bezerra P., Lu YX. (2020). Ultra-short-term and short-term heart rate variability recording during training camps and an international tournament in U-20 national futsal players. International Journal of Environmental Research and Public Health. 17(3), 775.
  • Li KHC., White FA., Tipoe T., Liu T., Wong MC., Jesuthasan A., Yan BP. (2019). The current state of mobile phone apps for monitoring heart rate, heart rate variability, and atrial fibrillation: narrative review. Journal of Medical Internet Research. 7(2), e11606.
  • Javaloyes A., Sarabia JM., Lamberts RP., Moya-Ramon M. (2019). Training prescription guided by heart-rate variability in cycling. International Journal of Sports Physiology and Performance. 14(1), 23-32.
  • Earnest CP., Jurca R., Church T., Chicharro JL., Hoyos J., Lucia A. (2004). Relation between physical exertion and heart rate variability characteristics in professional cyclists during the Tour of Spain. British Journal of Sports Medicine. 38(5), 568-575.
  • Pichot V., Roche F., Gaspoz JM., Enjolras F., Antoniadis A., Minini P., Barthelemy JC. (2000). Relation between heart rate variability and training load in middle-distance runners. Medicine and Science in Sports and Exercise. 32(10), 1729-1736.
  • Perrotta AS., Jeklin AT., Hives BA., Meanwell LE. Warburton DE. (2017). Validity of the elite HRV smartphone application for examining heart rate variability in a field-based setting. The Journal of Strength & Conditioning Research. 31(8), 2296-2302.
  • Bolkhovsky JB., Scully CG., Chon KH. (2012). Statistical analysis of heart rate and heart rate variability monitoring through the use of smart phone cameras. 1610-1613. 34th Annual International Conference of the IEEE EMBS. San Diego. California. USA.
  • Deelen I., Janssen M., Vos S., Kamphuis CBM., Ettema D. (2019). Attractive running environments for all? A cross-sectional study on physical environmental characteristics and runners' motives and attitudes, in relation to the experience of the running environment. Public Health. 19(1), 1-15.
  • Borgers J., Vanreusel B., Vos S., Forsberg P., Scheerder J. (2016). Do light sport facilities foster sports participation? A case study on the use of bark running tracks. International Journal of Sport Policy and Politics. 8(2), 287-304.
  • Hallmann K., Wicker P. (2012). Consumer profiles of runners at marathon races. International Journal of Event and Festival Management. 3(2), 171-187.
  • Scheerder J., Breedveld K., Borgers J. (2015). Running across Europe: the rise and size of one of the largest sport markets. 1. Edition. Palgrave Macmillan. New York (US), 1-3.
  • Shipway R., Holloway I. (2016). Health and the running body: Notes from an ethnography. International Review for the Sociology of Sport. 51(1), 78-96.
  • Vos S., Janssen M., Goudsmit J., Lauwerijssen C., Brombacher A. (2016). From problem to solution: Developing a personalized smartphone application for recreational runners following a three-step design approach. Procedia Engineering. 147, 799-805.
  • Vickey T., Breslin J., Williams A. (2013). Fitness-There's an App for That: Review of Mobile Fitness Apps. International Journal of Sport & Society 3(4), 1-20.
  • Keogh JW., Cox A., Anderson S., Liew B., Olsen A., Schram B., Furness, J. (2019). Reliability and validity of clinically accessible smartphone applications to measure joint range of motion: A systematic review. PloS One. 14(5), e0215806.
  • Keogh JW., Espinosa HG., Grigg J. (2016). Evolution of smart devices and human movement apps: recommendations for use in sports science education and practice. Journal of Fitness Research. 5(Special), 14-15.
  • Pourahmadi MR., Ebrahimi TI., Sarrafzadeh J., Bahramian M., Mohseni‐Bandpei MA., Rajabzadeh F., Taghipour M. (2017). Reliability and concurrent validity of a new iPhone goniometric application for measuring active wrist range of motion: a cross‐sectional study in asymptomatic subjects. Journal of Anatomy. 230(3), 484-495.
  • Mann JB., Thyfault JP., Ivey PA., Sayers SP. (2010). The effect of autoregulatory progressive resistance exercise vs. linear periodization on strength improvement in college athletes. The Journal of Strength & Conditioning Research. 24(7), 1718-1723.
  • Mann JB., Ivey PA., Sayers SP. (2015). Velocity-based training in football. Strength & Conditioning Journal. 37(6), 52-57.
  • Robertson RJ., Goss FL., Aaron DJ., Gairola A., Kowallis RA., Liu Y., White B. (2008). One repetition maximum prediction models for children using the OMNI RPE scale. The Journal of Strength & Conditioning Research. 22(1), 196-201.
  • Fry AC., Kraemer WJ. (1997). Resistance exercise overtraining and overreaching. Sports Medicine. 23(2), 106-129.
  • Loturco I., Ugrinowitsch C., Tricoli V., Pivetti B., Roschel H. (2013). Different loading schemes in power training during the preseason promote similar performance improvements in Brazilian elite soccer players. The Journal of Strength & Conditioning Research. 27(7), 1791-1797.
  • Kravitz L., Akalan C., Nowicki K., Kinzey SJ. (2003). Prediction of 1 repetition maximum in high-school power lifters. The Journal of Strength & Conditioning Research. 17(1), 167-172.
  • González-Badillo JJ., Sánchez-Medina L. (2010). Movement velocity as a measure of loading intensity in resistance training. International Journal of Sports Medicine. 31(5), 347-352.
  • Jidovtseff B., Harris NK., Crielaard JM., Cronin JB. (2011). Using the load-velocity relationship for 1RM prediction. The Journal of Strength & Conditioning Research. 25(1), 267-270.
  • Balsalobre-Fernández C., Marchante D., Muñoz-López M., Jiménez SL. (2018). Validity and reliability of a novel iPhone app for the measurement of barbell velocity and 1RM on the bench-press exercise. Journal of Sports Sciences. 36(1), 64-70.
  • Balsalobre-Fernández C., Marchante D., Baz-Valle E., Alonso-Molero, I., Jiménez SL., Muñóz-López M. (2017). Analysis of wearable and smartphone-based technologies for the measurement of barbell velocity in different resistance training exercises. Frontiers in Physiology, 649.
  • Cetin O., Isik O. (2021). Validity and reliability of mylift app in determining 1-rm for deadlift and back squat exercises. European Journal of Human Movement. 46, 28-36.
  • García-Ramos A., Pestaña-Melero FL., Pérez-Castilla A., Rojas FJ., Haff GG. (2018). Mean velocity vs. mean propulsive velocity vs. peak velocity: which variable determines bench press relative load with higher reliability? The Journal of Strength & Conditioning Research. 32(5), 1273-1279.
  • Jovanović M., Flanagan EP. (2014). Researched applications of velocity based strength training. Journal of Australian Strength and Conditioning. 22(2), 58-69.
  • Clemente FM., Akyildiz Z., Pino-Ortega J., Rico-González M. (2021). Validity and reliability of the inertial measurement unit for barbell velocity assessments: A systematic review. Sensors. 21(7), 2511.
  • Rey E., Barcala-Furelos R., Padron-Cabo A. (2017). Liza Plus for neuromuscular assessment and training: mobile app user guide. British Journal of Sports Medicine. 51(13), 1044-1045.
  • Nolan M., Mitchell JR., Doyle-Baker PK. (2014). Validity of the Apple iPhone®/iPod Touch® as an accelerometer-based physical activity monitor: a proof-of-concept study. Journal of Physical Activity and Health. 11(4), 759-769.
  • İzzet İ., Çalışkan G., Ayılgan E. (2018). Olimpik halter kaldırışlarının bazı biyomekanik ölçümlerinde kullanılan Android BarSense yazılımının geçerliği. Gazi Beden Eğitimi ve Spor Bilimleri Dergisi. 23(3), 171-182.
  • Pérez-Castilla A., Boullosa D., García-Ramos A. (2021). Reliability and validity of the iLOAD application for monitoring the mean set velocity during the back squat and bench press exercises performed against different loads. The Journal of Strength & Conditioning Research. 35, 57-65.
  • De Sá EC., Medeiros AR., Ferreira AS., Ramos AG., Janicijevic D., Boullosa D. (2019). Validity of the iLOAD® app for resistance training monitoring. PeerJ. 7, e7372.
  • Cruvinel-Cabral RM., Oliveira-Silva I., Medeiros AR., Claudino JG., Jiménez-Reyes P., Boullosa DA. (2018). The validity and reliability of the “My Jump App” for measuring jump height of the elderly. PeerJ. 6, e5804.
  • Gallardo-Fuentes F., Gallardo-Fuentes J., Ramírez-Campillo R., Balsalobre-Fernández C., Martínez C., Caniuqueo A., Izquierdo M. (2016). Intersession and intrasession reliability and validity of the My Jump app for measuring different jump actions in trained male and female athletes. Journal of Strength and Conditioning Research. 30(7), 2049-2056.
  • Stanton R., Kean CO., Scanlan AT. (2015). My Jump for vertical jump assessment. British Journal of Sports Medicine. 49(17), 1157-1158.
  • Balsalobre-Fernández C., Glaister M., Lockey RA. (2015). The validity and reliability of an iPhone app for measuring vertical jump performance. Journal of Sports Sciences. 33(15), 1574-1579.
  • Sharp AP., Cronin JB. Neville J. (2019). Using smartphones for jump diagnostics: A brief review of the validity and reliability of the my jump app. Strength & Conditioning Journal. 41(5), 96-107.
  • Haynes T., Bishop C., Antrobus M., Brazier J. (2019). The validity and reliability of the My Jump 2 app for measuring the reactive strength index and drop jump performance. The Journal of Sports Medicine and Physical Fitness. 59(2), 253-258.
  • Haugen T., Buchheit M. (2016). Sprint running performance monitoring: methodological and practical considerations. Sports Medicine. 46(5), 641-656.
  • Faude O., Koch T. Meyer T. (2012). Straight sprinting is the most frequent action in goal situations in professional football. Journal of Sports Sciences. 30(7), 625-631.
  • Rabita G., Dore S., Slawinski J., Sàez‐de‐Villarreal E., Couturier A., Samozino P., Morin JB. (2015). Sprint mechanics in world‐class athletes: a new insight into the limits of human locomotion. Scandinavian Journal of Medicine & Science in Sports. 25(5), 583-594.
  • Romero-Franco N., Jiménez-Reyes P., Castaño-Zambudio A., Capelo-Ramírez F., Rodríguez-Juan JJ., González-Hernández J., Balsalobre-Fernández C. (2017). Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods. European Journal of Sport Science. 17(4), 386-392.
  • Stanton R., Hayman M., Humphris N., Borgelt H., Fox J., Del Vecchio L., Humphries B. (2016). Validity of a smartphone-based application for determining sprinting performance. Journal of Sports Medicine. 7, 1-5.
  • Brughelli M., Cronin J., Levin G., Chaouachi A. (2008). Understanding change of direction ability in sport. Sports Medicine. 38(12), 1045-1063.
  • Sheppard JM., Young WB. (2006). Agility literature review: Classifications, training and testing. Journal of Sports Sciences. 24(9), 919-932.
  • Balsalobre-Fernández C., Bishop C., Beltrán-Garrido JV., Cecilia-Gallego P., Cuenca-Amigó A., Romero-Rodríguez D., Madruga-Parera M. (2019). The validity and reliability of a novel app for the measurement of change of direction performance. Journal of Sports Sciences. 37(21), 2420-2424.
  • Chen Z., Bian C., Liao K., Bishop C., Li Y. (2021). Validity and reliability of a phone App and stopwatch for the measurement of 505 change of direction performance: a test-retest study design. Frontiers in Physiology 12, 743800
  • Rangasamy K., As' ari MA., Rahmad NA., Ghazali NF., Ismail S. (2020). Deep learning in sport video analysis: a review. Telkomnika. 18(4), 1926-1933.
Toplam 69 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Spor Hekimliği
Bölüm Case Report
Yazarlar

Onat Çetin 0000-0001-6841-5518

Selman Kaya 0000-0002-2185-6436

Proje Numarası -
Yayımlanma Tarihi 16 Mart 2022
Gönderilme Tarihi 16 Şubat 2022
Kabul Tarihi 15 Mart 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 16 Sayı: 1

Kaynak Göster

APA Çetin, O., & Kaya, S. (2022). ATLETİK PERFORMANS ÖLÇÜMÜNDE VE TAKİBİNDE KULLANILAN MOBİL UYGULAMALAR: GELENEKSEL BİR DERLEME. Beden Eğitimi Ve Spor Bilimleri Dergisi, 16(1), 1-21.

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