Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living
Abstract
:1. Introduction
2. Monitoring Parameters of External and Internal Load
3. Monitoring External Parameters
3.1. The Duration and Frequency of Training Sessions
3.2. Distance Covered
3.3. Short Explosive Activities
3.4. Environmental Factors
3.5. Sleep
3.6. Physical Activity Off-Training
4. Monitoring Internal Load
4.1. Parameters of General Health
4.2. Parameters Related to Cardiac Dynamics and Stress
4.3. Parameters Related to Bio-Psychological Stress
4.4. Subjective Parameters
4.5. Neuromuscular Variables
4.6. Parameters Related to Metabolism
5. Practical Procedure for Monitoring Relevant Parameters
6. Practical Considerations
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Skinner, J.S.; Wilmore, K.M.; Krasnoff, J.B.; Jaskolski, A.; Jaskolska, A.; Gagnon, J.; Province, M.A.; Leon, A.S.; Rao, D.C.; Wilmore, J.H.; et al. Adaptation to a standardized training program and changes in fitness in a large, heterogeneous population: The HERITAGE Family Study. Med. Sci. Sports Exerc. 2000, 32, 157–161. [Google Scholar] [CrossRef] [PubMed]
- Kiely, J. Periodization Theory: Confronting an Inconvenient Truth. Sports Med. 2018, 48, 753–764. [Google Scholar] [CrossRef] [PubMed]
- Soligard, T.; Schwellnus, M.; Alonso, J.M.; Bahr, R.; Clarsen, B.; Dijkstra, H.P.; Gabbett, T.; Gleeson, M.; Hägglund, M.; Hutchinson, M.R. How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br. J. Sports Med. 2016, 50, 1030–1041. [Google Scholar] [CrossRef] [PubMed]
- Halson, S.L. Monitoring training load to understand fatigue in athletes. Sports Med. 2014, 44, S139–S147. [Google Scholar] [CrossRef] [PubMed]
- Mujika, I. Quantification of Training and Competition Loads in Endurance Sports: Methods and Applications. Int. J. Sports Physiol. Perform. 2017, 12, S2-9–S2-17. [Google Scholar] [CrossRef] [PubMed]
- Sperlich, B.; Holmberg, H.C. The Responses of Elite Athletes to Exercise: An All-Day, 24-h Integrative View Is Required! Front. Physiol. 2017, 8, 564. [Google Scholar] [CrossRef] [PubMed]
- Starling, L.T.; Lambert, M.I. Monitoring Rugby Players for Fitness and Fatigue: What Do Coaches Want? Int. J. Sports Physiol. Perform. 2017, 15, 1–30. [Google Scholar] [CrossRef] [PubMed]
- Düking, P.; Hotho, A.; Holmberg, H.C.; Fuss, F.K.; Sperlich, B. Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies. Front. Physiol. 2016, 7, 71. [Google Scholar] [CrossRef] [PubMed]
- Luppa, P.B.; Bietenbeck, A.; Beaudoin, C.; Giannetti, A. Clinically relevant analytical techniques, organizational concepts for application and future perspectives of point-of-care testing. Biotechnol. Adv. 2016, 34, 139–160. [Google Scholar] [CrossRef] [PubMed]
- Düking, P.; Holmberg, H.C.; Sperlich, B. Instant biofeedback provided by wearable sensor technology can help to optimize exercise and prevent injury and overuse. Front. Physiol. 2017, 8, 167. [Google Scholar] [CrossRef] [PubMed]
- Saw, A.E.; Main, L.C.; Gastin, P.B. Monitoring the athlete training response: Subjective self-reported measures trump commonly used objective measures: A systematic review. Br. J. Sports Med. 2016, 50, 281–291. [Google Scholar] [CrossRef] [PubMed]
- Colby, M.J.; Dawson, B.; Heasman, J.; Rogalski, B.; Gabbett, T.J. Accelerometer and GPS-derived running loads and injury risk in elite Australian footballers. J. Strength Cond. Res. 2014, 28, 2244–2252. [Google Scholar] [CrossRef] [PubMed]
- Gabbett, T.J. The training-injury prevention paradox: Should athletes be training smarter and harder? Br. J. Sports Med. 2016, 50, 273–280. [Google Scholar] [CrossRef] [PubMed]
- Ehrmann, F.E.; Duncan, C.S.; Sindhusake, D.; Franzsen, W.N.; Greene, D.A. GPS and Injury Prevention in Professional Soccer. J. Strength Cond. Res. 2016, 30, 360–367. [Google Scholar] [CrossRef] [PubMed]
- Akenhead, R.; French, D.; Thompson, K.G.; Hayes, P.R. The physiological consequences of acceleration during shuttle running. Int. J. Sports Med. 2015, 36, 302–307. [Google Scholar] [CrossRef] [PubMed]
- Kelly, D.; Coughlan, G.F.; Green, B.S.; Caulfield, B. Automatic detection of collisions in elite level rugby union using a wearable sensing device. Sports Eng. 2012, 15, 81–92. [Google Scholar] [CrossRef]
- Cardinale, M.; Varley, M.C. Wearable Training-Monitoring Technology: Applications, Challenges, and Opportunities. Int. J. Sports Physiol. Perform. 2017, 12, S255–S2629. [Google Scholar] [CrossRef] [PubMed]
- Murray, N.B.; Black, G.M.; Whiteley, R.J.; Gahan, P.; Cole, M.H.; Utting, A.; Gabbett, T.J. Automatic Detection of Pitching and Throwing Events in Baseball With Inertial Measurement Sensors. Int. J. Sports Physiol. Perform. 2017, 12, 533–537. [Google Scholar] [CrossRef] [PubMed]
- Hendricks, S.; Lambert, M.I. Theoretical Model Describing the Relationship between the Number of Tackles in Which A Player Engages, Tackle Injury Risk and Tackle Performance. J. Sports Sci. Med. 2014, 13, 715–717. [Google Scholar] [PubMed]
- Hargreaves, M. Physiological limits to exercise performance in the heat. J. Sci. Med. Sport/Sports Med. Aust. 2008, 11, 66–71. [Google Scholar] [CrossRef] [PubMed]
- Born, D.P.; Hoppe, M.W.; Lindner, N.; Freiwald, J.; Holmberg, H.C.; Sperlich, B. Adaptive mechanisms and behavioural recommendations: Playing football in heat, cold and high altitude conditions. Sportverletzung Sportschaden: Organ der Gesellschaft fur Orthopadisch-Traumatologische Sportmedizin 2014, 28, 17–23. [Google Scholar] [CrossRef]
- Taylor, L.; Chrismas, B.C.; Dascombe, B.; Chamari, K.; Fowler, P.M. The Importance of Monitoring Sleep within Adolescent Athletes: Athletic, Academic, and Health Considerations. Front. Physiol. 2016, 7, 101. [Google Scholar] [CrossRef] [PubMed]
- Fullagar, H.H.; Skorski, S.; Duffield, R.; Hammes, D.; Coutts, A.J.; Meyer, T. Sleep and athletic performance: The effects of sleep loss on exercise performance, and physiological and cognitive responses to exercise. Sports Med. 2015, 45, 161–186. [Google Scholar] [CrossRef] [PubMed]
- Min, Y.H.; Lee, J.W.; Shin, Y.W.; Jo, M.W.; Sohn, G.; Lee, J.H.; Lee, G.; Jung, K.H.; Sung, J.; Ko, B.S.; et al. Daily collection of self-reporting sleep disturbance data via a smartphone app in breast cancer patients receiving chemotherapy: A feasibility study. J. Med. Internet Res. 2014, 16, e135. [Google Scholar] [CrossRef] [PubMed]
- Chen, Z.; Lin, M.; Chen, F.; Lane, N.D.; Cardone, G.; Wang, R.; Li, T.; Chen, Y.; Choudhury, T.; Campbel, A.T. Unobtrusive sleep monitoring using smartphones. In Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Venice, Italy, 5–8 May 2013. [Google Scholar]
- Burr, J.F.; Slysz, J.T.; Boulter, M.S.; Warburton, D.E. Influence of Active Recovery on Cardiovascular Function During Ice Hockey. Sports Med. Open 2015, 1, 27. [Google Scholar] [CrossRef] [PubMed]
- Sperlich, B.; Becker, M.; Hotho, A.; Wallmann-Sperlich, B.; Sareban, M.; Winkert, K.; Steinacker, J.M.; Treff, G. Sedentary Behavior among National Elite Rowers during Off-Training—A Pilot Study. Front. Physiol. 2017, 8, 655. [Google Scholar] [CrossRef] [PubMed]
- DeMasi, O.; Feygin, S.; Dembo, A.; Aguilera, A.; Recht, B. Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study. JMIR mHealth uHealth 2017, 5, e137. [Google Scholar] [CrossRef] [PubMed]
- Wahl, Y.; Düking, P.; Droszez, A.; Wahl, P.; Mester, J. Criterion-Validity of Commercially Available Physical Activity Tracker to Estimate Step Count, Covered Distance and Energy Expenditure during Sports Conditions. Front. Physiol. 2017, 8, 725. [Google Scholar] [CrossRef] [PubMed]
- Noakes, T. Fluid replacement during marathon running. Clin. J. Sport Med. 2003, 13, 309–318. [Google Scholar] [CrossRef] [PubMed]
- Nakamura, K. Central circuitries for body temperature regulation and fever. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2011, 301, R1207–R1228. [Google Scholar] [CrossRef] [PubMed]
- Horn, P.L.; Pyne, D.B.; Hopkins, W.G.; Barnes, C.J. Lower white blood cell counts in elite athletes training for highly aerobic sports. Eur. J. Appl. Physiol. 2010, 110, 925–932. [Google Scholar] [CrossRef] [PubMed]
- Born, D.P.; Faiss, R.; Willis, S.J.; Strahler, J.; Millet, G.P.; Holmberg, H.C.; Sperlich, B. Circadian variation of salivary immunoglobin A, alpha-amylase activity and mood in response to repeated double-poling sprints in hypoxia. Eur. J. Appl. Physiol. 2016, 116, 1–10. [Google Scholar] [CrossRef] [PubMed]
- Gomes, E.C.; Silva, A.N.; de Oliveira, M.R. Oxidants, antioxidants, and the beneficial roles of exercise-induced production of reactive species. Oxid. Med. Cell. Longev. 2012, 2012, 756132. [Google Scholar] [CrossRef] [PubMed]
- Peeling, P.; Dawson, B.; Goodman, C.; Landers, G.; Trinder, D. Athletic induced iron deficiency: New insights into the role of inflammation, cytokines and hormones. Eur. J. Appl. Physiol. 2008, 103, 381–391. [Google Scholar] [CrossRef] [PubMed]
- Hinton, P.S. Iron and the endurance athlete. Appl. Physiol. Nutr. Metab. 2014, 39, 1012–1081. [Google Scholar] [CrossRef] [PubMed]
- Buchheit, M. Monitoring training status with HR measures: Do all roads lead to Rome? Front. Physiol. 2014, 5, 73. [Google Scholar] [CrossRef] [PubMed]
- Aubert, A.E.; Seps, B.; Beckers, F. Heart rate variability in athletes. Sports Med. 2003, 33, 889–919. [Google Scholar] [CrossRef] [PubMed]
- Achten, J.; Jeukendrup, A.E. Heart rate monitoring: Applications and limitations. Sports Med. 2003, 33, 517–538. [Google Scholar] [CrossRef] [PubMed]
- Dong, J.G. The role of heart rate variability in sports physiology. Exp. Ther. Med. 2016, 11, 1531–1536. [Google Scholar] [CrossRef] [PubMed]
- Plews, D.J.; Laursen, P.B.; Le Meur, Y.; Hausswirth, C.; Kilding, A.E.; Buchheit, M. Monitoring training with heart rate-variability: How much compliance is needed for valid assessment? Int. J. Sports Physiol. Perform. 2014, 9, 783–790. [Google Scholar] [CrossRef] [PubMed]
- Le Meur, Y.; Buchheit, M.; Aubry, A.; Coutts, A.J.; Hausswirth, C. Assessing Overreaching with HRR: What is the Minimal Exercise Intensity Required? Int. J. Sports Physiol. Perform. 2017, 12, 569–573. [Google Scholar] [CrossRef] [PubMed]
- Achtzehn, S. POCT-Patientennahe Labordiagnostik; Luppa, P.B., Junker, R., Eds.; Springer Verlag: New York, NY, USA, 2017. [Google Scholar]
- Dimitriou, L.; Sharp, N.C.; Doherty, M. Circadian effects on the acute responses of salivary cortisol and IgA in well trained swimmers. Br. J. Sports Med. 2002, 36, 260–264. [Google Scholar] [CrossRef] [PubMed]
- Rohleder, N.; Nater, U.M. Determinants of salivary alpha-amylase in humans and methodological considerations. Psychoneuroendocrinology 2009, 34, 469–485. [Google Scholar] [CrossRef] [PubMed]
- Papacosta, E.; Nassis, G.P. Saliva as a tool for monitoring steroid, peptide and immune markers in sport and exercise science. J. Sci. Med. Sport/Sports Med. Aust. 2011, 14, 424–434. [Google Scholar] [CrossRef] [PubMed]
- McLellan, C.P.; Lovell, D.I.; Gass, G.C. Markers of postmatch fatigue in professional Rugby League players. J. Strength Cond. Res./Natl. Strength Cond. Assoc. 2011, 25, 1030–1039. [Google Scholar] [CrossRef] [PubMed]
- Koibuchi, E.; Suzuki, Y. Exercise upregulates salivary amylase in humans (Review). Exp. Ther. Med. 2014, 7, 773–777. [Google Scholar] [CrossRef] [PubMed]
- Nater, U.M.; Rohleder, N.; Schlotz, W.; Ehlert, U.; Kirschbaum, C. Determinants of the diurnal course of salivary alpha-amylase. Psychoneuroendocrinology 2007, 32, 392–401. [Google Scholar] [CrossRef] [PubMed]
- Sargent, C.; Lastella, M.; Halson, S.L.; Roach, G.D. The impact of training schedules on the sleep and fatigue of elite athletes. Chronobiol. Int. 2014, 31, 1160–1168. [Google Scholar] [CrossRef] [PubMed]
- Foster, C.; Florhaug, J.A.; Franklin, J.; Gottschall, L.; Hrovatin, L.A.; Parker, S.; Doleshal, P.; Dodge, C. A new approach to monitoring exercise training. J. Strength Cond. Res./Natl. Strength Cond. Assoc. 2001, 15, 109–115. [Google Scholar]
- Kellmann, M. Preventing overtraining in athletes in high-intensity sports and stress/recovery monitoring. Scand. J. Med. Sci. Sports 2010, 20 (Suppl. 2), 95–102. [Google Scholar] [CrossRef] [PubMed]
- Abbiss, C.R.; Laursen, P.B. Models to explain fatigue during prolonged endurance cycling. Sports Med. 2005, 35, 865–898. [Google Scholar] [CrossRef] [PubMed]
- Brancaccio, P.; Lippi, G.; Maffulli, N. Biochemical markers of muscular damage. Clin. Chem. Lab. Med. 2010, 48, 757–767. [Google Scholar] [CrossRef] [PubMed]
- Banfi, G.; Colombini, A.; Lombardi, G.; Lubkowska, A. Metabolic markers in sports medicine. Adv. Clin. Chem. 2012, 56, 1–54. [Google Scholar] [PubMed]
- Born, D.P.; Stoggl, T.; Swaren, M.; Bjorklund, G. Running in Hilly Terrain: NIRS is More Accurate to Monitor Intensity than Heart Rate. Int. J. Sports Physiol. Perform. 2016, 24, 1–21. [Google Scholar] [CrossRef]
- Meister, S.; Faude, O.; Ammann, T.; Schnittker, R.; Meyer, T. Indicators for high physical strain and overload in elite football players. Scand. J. Med. Science Sports 2013, 23, 156–1633. [Google Scholar] [CrossRef] [PubMed]
- Urhausen, A.; Kindermann, W. Diagnosis of overtraining: What tools do we have? Sports Med. 2002, 32, 95–102. [Google Scholar] [CrossRef] [PubMed]
- Borges, N.R.; Driller, M.W. Wearable Lactate Threshold Predicting Device is Valid and Reliable in Runners. J. Strength Cond. Res./Natl. Strength Cond. Assoc. 2016, 30, 2212–2218. [Google Scholar] [CrossRef] [PubMed]
- Faude, O.; Kindermann, W.; Meyer, T. Lactate threshold concepts: How valid are they? Sports Med. 2009, 39, 469–490. [Google Scholar] [CrossRef] [PubMed]
- Hayes, L.D.; Bickerstaff, G.F.; Baker, J.S. Interactions of cortisol, testosterone, and resistance training: Influence of circadian rhythms. Chronobiol. Int. 2010, 27, 675–705. [Google Scholar] [CrossRef] [PubMed]
- Brud, L. Amendments to the Laws of the Game—2015/2016 and Information on the Completed Reform of The International Football Association Board. 2015. Available online: http://resources.fifa.com/mm/document/affederation/ifab/02/60/91/38/circular_log_amendments_2015_v1.0_en_neutral.pdf (accessed on 19 February 2017).
- Gao, W.; Emaminejad, S.; Nyein, H.Y.Y.; Challa, S.; Chen, K.; Peck, A.; Fahad, H.M.; Ota, H.; Shiraki, H.; Kiriya, D.; et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 2016, 529, 509–514. [Google Scholar] [CrossRef] [PubMed]
- Kantoch, E.; Augustyniak, P.; Markiewicz, M.; Prusak, D. Monitoring activities of daily living based on wearable wireless body sensor network. Conf. Proc. Eng. Med. Biol. Soc. 2014, 2014, 586–589. [Google Scholar] [CrossRef]
- Luppa, P.B.; Proll, G.; Imhoff, M.; Koschinsky, T. Analytische Verfahren, Biosensortechnologie. In POCT-Patientennahe Labordiagnostik; Springer: New York, NY, USA, 2017; pp. 39–49. [Google Scholar]
- Rosenberger, M.E.; Buman, M.P.; Haskell, W.L.; McConnell, M.V.; Carstensen, L.L. Twenty-four Hours of Sleep, Sedentary Behavior, and Physical Activity with Nine Wearable Devices. Med. Sci. Sports Exerc. 2016, 48, 457–465. [Google Scholar] [CrossRef] [PubMed]
- Austen, K. What could derail the wearables revolution? Nature 2015, 525, 22–24. [Google Scholar] [CrossRef] [PubMed]
- Sperlich, B.; Holmberg, H.C. Wearable, yes, but able...?: It is time for evidence-based marketing claims! Br. J. Sports Med. 2017, 51, 1240. [Google Scholar] [CrossRef] [PubMed]
- Düking, P.; Fuss, F.K.; Holmberg, H.C.; Sperlich, B. Recommendations for Assessment of the Reliability, Sensitivity, and Validity of Data Provided by Wearable Sensors Designed for Monitoring Physical Activity. JMIR mHealth and uHealth 2018, 6, e102. [Google Scholar] [CrossRef] [PubMed]
Type of Parameter | Individual Parameters | Method/Sensor Technology | Additional Comments |
---|---|---|---|
Duration and frequency of training sessions |
| Sport watches | Sport watches allow automatic storage of data in the “cloud” |
Distance covered (in different speed zones) | e.g.,
| Global Navigation Satellite Systems |
|
Local positioning systems | In- and outdoors | ||
Short explosive activities | e.g.,
| Inertial measurement units | Embedded in a Global Navigation Satellite System receiver unit |
Sleep |
| Actigraphy | Actigraphy should only be used with caution to access sleep quality. |
Environmental factors |
|
|
Type of Parameter | Individual Parameter | Area of Interest |
---|---|---|
General health | Core, body or skin temperature | Thermoregulation |
White blood cell count | Infections | |
High-sensitive C-reactive Protein | Inflammation | |
Immunoglobulin A (IglA) | Mucosal immune function | |
Reactive Oxygen Species | Oxidative stress | |
Haemoglobin | Anaemia and dehydration | |
Ferritin | Iron deficiency | |
Bio-psychological stress | Cortisol |
|
Alpha-amylase | Stress on the sympathetic nervous system | |
Subjective parameters | Questionnaires and diaries | Various psychological aspects |
Parameters of cardiac stress | Cardiac troponin | Myocardial stress |
Fatty acid-binding protein | ||
Heart rate during exercise | ||
Heart rate variability | Cardiac autonomous nervous system | |
Heart rate recovery | Overreaching | |
Parameters of muscle damage | Aspartate aminotransferase | Breakdown of muscle cell structureProtein catabolism |
Creatine kinase | ||
Myoglobin | ||
Lactate dehydrogenase | ||
Parameters of metabolism | Lactate | Endurance performance |
Urea | Elevated protein catabolism | |
Uric acid | Enhanced metabolic strain when muscle stores of glycogen are depleted | |
Creatinine | Renal functioning | |
Testosterone | Non-functional overreaching | |
Tissue oxygenation | Intensity of effort | |
pH | Acid-base status |
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Düking, P.; Achtzehn, S.; Holmberg, H.-C.; Sperlich, B. Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living. Sensors 2018, 18, 1632. https://doi.org/10.3390/s18051632
Düking P, Achtzehn S, Holmberg H-C, Sperlich B. Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living. Sensors. 2018; 18(5):1632. https://doi.org/10.3390/s18051632
Chicago/Turabian StyleDüking, Peter, Silvia Achtzehn, Hans-Christer Holmberg, and Billy Sperlich. 2018. "Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living" Sensors 18, no. 5: 1632. https://doi.org/10.3390/s18051632
APA StyleDüking, P., Achtzehn, S., Holmberg, H. -C., & Sperlich, B. (2018). Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living. Sensors, 18(5), 1632. https://doi.org/10.3390/s18051632