Effects of palm cooling on thermoregulatory-related and subjective indicators during exercise in a hot environment.

Palm cooling is a simple and easily implemented intervention strategy during exercise. We aimed to examine the effects of bilateral palm cooling before and during exercise on thermoregulatory-related and subjective indicators in a hot environment. Ten active men (age: 21 ± 1 years; height 172.2 ± 5.7 cm; weight 67.4 ± 7.2 kg) underwent three experimental trials at the same time of the day, consisting of palm cooling with 12°C (ICE12°C), palm cooling with 0°C (ICE0°C) where vasoconstriction is supposed to occur, and control (CON) trials. After 30 min rest at ambient temperature, participants performed 20 min exercise at 33°C, 60% relative humidity. Rectal temperature, skin temperature, rate of perceived exertion, heart rate, local sweat rate, oxygen uptake, carbon dioxide production, and respiratory exchange ratio did not differ between the trials. Thermal sensation and comfort were lower in the ICE12°C and ICE0°C trials than in the CON trial, but the ICE0°C trial showed a longer duration of cold sensation than the ICE12°C trial. Palm cooling at 12°C and 0°C improved thermal sensation and thermal comfort during exercise in a hot environment, although there was no effect on core body temperature, sweating, and cardiorespiratory function. Bilateral palm cooling at 12°C and 0°C improve subjective indicators during exercise in a hot environment and these effects are slightly greater at 0°C than at 12°C cooling, while having no effect on thermoregulatory-related indicators. These results suggest that bilateral palm cooling at lower temperatures may safely reduce the perception of warmth during exercise in a hot environment.

Automatic Identification of Subtechniques in Skating-Style Roller Skiing Using Inertial Sensors.

This study aims to develop and validate an automated system for identifying skating-style cross-country subtechniques using inertial sensors. In the first experiment, the performance of a male cross-country skier was used to develop an automated identification system. In the second, eight male and seven female college cross-country skiers participated to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, and a small video camera on a backpack. All subjects skied through a 3450 m roller ski course using a skating style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, as well as by visual observations from a video recording of the same ski run. The system correctly identified 6418 subtechniques from a total of 6768 cycles, which indicates an accuracy of 94.8%. The precisions of the automatic system for identifying the V1R, V1L, V2R, V2L, V2AR, and V2AL subtechniques were 87.6%, 87.0%, 97.5%, 97.8%, 92.1%, and 92.0%, respectively. Most incorrect identification cases occurred during a subtechnique identification that included a transition and turn event. Identification accuracy can be improved by separately identifying transition and turn events. This system could be used to evaluate each skier's subtechniques in course conditions.

Automated identification and evaluation of subtechniques in classical-style roller skiing.

The aims of the present study were (1) the development of an automated system for identifying classical-style ski subtechniques using angular rate sensors, and (2) the determination of the relationships among skiing velocity, ski course conditions, and ski subtechniques using a global navigation satellite system (GNSS) and the developed automated identification system. In the first experiment, the performance of a male cross-country skier was used to develop an automated system for identifying classical-style ski subtechniques. In the second one, the performances of five male and five female college cross-country skiers were used to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, a small video camera on the helmet, and a GNSS receiver. All subjects skied a 6,900-m roller ski course using the classical-style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, and also by visual count from a video recording of the same ski run. The results showed that the automated identification method could be definitively used to recognize various subtechniques. Specifically, the system correctly identified 9,307 subtechnique cycles out of a total of 9,444 counted visually, which indicated an accuracy of 98.5%. We also measured the skiing velocity and the course slope using the GNSS module. The data was then used to determine the subtechnique distributions as a function of the inclination and skiing velocity. It was observed that male and female skiers selected double poling below 6.7° and 5.5° uphill, respectively. In addition, male and female skiers selected diagonal stride above 0.7° and 2.5° uphill, and below 5.4 m/s and 4.5 m/s velocity, respectively. These results implied that the subtechnique distribution plot could be used to analyze the technical characteristics of each skier. Key PointsThe automatic identification method, which utilizes data obtained by small and light inertial sensors, could be used to recognize subtechniques of classical-style roller skiing with a high accuracy of 98.5%.The skiing velocity was measured using a small DGNSS module at all over the course, which made it possible to evaluate the technical features of skiers together with the results of the automatic identification.However, there were limitations in the automatic identification during the start phase, the downhill, and the transition period between subtechniques.