DESIGNING SMART TREADMILL FOR ATHLETIC ENDURANCE TRAINING

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MEAMARBASHI ABBAS; SIAHKOUHIAN MAREFAT

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Paper Information

Journal: JOURNAL OF ADVANCED SPORT TECHNOLOGY Year:2017 | Volume:1 | Issue:2 Page(s): 30-32

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Information Journal Paper

Title

DESIGNING SMART TREADMILL FOR ATHLETIC ENDURANCE TRAINING

Author(s)

MEAMARBASHI ABBAS | SIAHKOUHIAN MAREFAT | Issue Writer Certificate

Keywords

DESIGN AND MANUFACTURE

HARDWARE

SOFTWARE

TREADMILL

CARDIORESPIRATORY FITNESS

Abstract

Using treadmill and cycle ergometers are the best methods of endurance training and choosing besttraining intensity is very crucial in endurance exercise training. According to more than one decade of ourresearch experiences, it is possible to determine optimum personal training intensity based on estimationof person's anaerobic threshold. A hardware and software has been developed to monitor the heart rateand control the treadmill speed and slope. Software provided utilities to record the individual information(e.g. name, age, gender, weight and maximum and resting heart rate) and graphical curves of treadmill(speed, slope, work, power) and real-time heart rate. In this method, heart rate was used to draw the heartrate-time curve during an exhaustive graded maximal intensity exercise to find the best treadmill speedand slope in his/her anaerobic threshold. In this study, ten male athletes (19.3±1.7 years; 88.50±4.43 kg;182.0±3.7 cm) recruited. Validity and reliability of this method have been evaluated by gas analysis every5 seconds to determine anaerobic threshold and compare it with the Heart Rate Deflection Point (HRDP)calculated by the software on a standard Treadmill protocol during two sessions with one week rest.Bland-Altman and Intraclass Correlation Coefficients (ICC) was used to find any agreement between thetwo methods and Test-Retest was used to prove the reliability of the method. There was a very highagreement between two methods (±1.96; 95% CI = -16.5 to +37.5 b/min) and calculate anaerobicthreshold had a positive and significant correlation (r=0.932; p<0.001). Feasibility of design a hardwareand software and validity and reliability of estimated individual anaerobic threshold ascertained. It is areasonably low price hardware and software recommendable to implement in future treadmillmanufacturing.

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APA: Copy

MEAMARBASHI, ABBAS, & SIAHKOUHIAN, MAREFAT. (2017). DESIGNING SMART TREADMILL FOR ATHLETIC ENDURANCE TRAINING. JOURNAL OF ADVANCED SPORT TECHNOLOGY, 1(2 ), 30-32. SID. https://sid.ir/paper/267607/en

Vancouver: Copy

MEAMARBASHI ABBAS, SIAHKOUHIAN MAREFAT. DESIGNING SMART TREADMILL FOR ATHLETIC ENDURANCE TRAINING. JOURNAL OF ADVANCED SPORT TECHNOLOGY[Internet]. 2017;1(2 ):30-32. Available from: https://sid.ir/paper/267607/en

IEEE: Copy

ABBAS MEAMARBASHI, and MAREFAT SIAHKOUHIAN, “DESIGNING SMART TREADMILL FOR ATHLETIC ENDURANCE TRAINING,” JOURNAL OF ADVANCED SPORT TECHNOLOGY, vol. 1, no. 2 , pp. 30–32, 2017, [Online]. Available: https://sid.ir/paper/267607/en

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