Outdoor Running Research Articles

Comparison of inertial-based filters for orientation estimation in indoor and outdoor running

Comparison of inertial-based filters for orientation estimation in indoor and outdoor running

A Simple and Sensitive Wearable SERS Sensor Utilizing Plasmonic-Active Gold Nanostars.

Wearable sweat sensors hold great potential for offering detailed health insights by monitoring various biomarkers present in sweat, such as glucose, lactate, uric acid, and urea, in real time. However, most previously reported sensors, primarily based on electrochemical technology, are limited to monitoring only a single analyte at a given time. This study introduces a simple, sensitive, wearable patch based on surface-enhanced Raman spectroscopy (SERS), integrated with highly plasmonically active sharp-branched gold nanostars (GNS) for the simultaneous detection of three sweat biomarkers: lactate, urea, and glucose. We have fabricated the GNS on commercially available adhesive tape, resulting in achieving a low-cost, flexible, and adhesive wearable SERS patch. The limits of detection for lactate, urea, and glucose were achieved at 0.7, 0.6, and 0.7 μM, respectively, which are significantly lower than the clinically relevant concentrations of these biomarkers in sweat. We further evaluated the performance of our wearable SERS patch during outdoor activities, including sitting, walking, and running. To evaluate its overall effectiveness, we simultaneously measured the concentrations of lactate, urea, and glucose during these activities. Overall, our simple, sensitive wearable SERS sensor represents a significant breakthrough by enabling the simultaneous detection of lactate, urea, and glucose present in sweat, marking a major step toward future applications in autonomous and noninvasive personalized healthcare monitoring at home.

Differences in the stride time and lower limb joint angles and their variability during distance running between treadmill and over-ground: a crossover study.

Treadmills have been used in laboratories to assess various measures related to walking and running. However, there has been some skepticism regarding their reliability as a representation of outdoor running. While marathon running has gained popularity as a form of physical activity, there have been few studies examining stride-to-stride variability after distance running, especially in relation to the duration and surface of running. This study compared stride time and lower limb joint angles during distance treadmill running and running over-ground. The hypothesis was that stride-to-stride variability would be influenced by running duration and surface, with greater variability observed during outdoor running. Eleven runners participated in the study, running on a treadmill and over-ground for 31 minutes at their preferred speed. Inertial measurement units were used to measure stride time, total range of motion, and joint angles of the hip, knee, and ankle in different phases of the gait cycle in the sagittal plane movements. Mean and coefficient of variation of each parameter were compared between the initial and final 5 minutes of running on the treadmill and over-ground. There were no significant differences in stride time or its variability based on running duration or surface. However, mean and variability of certain lower limb joint angles were higher during outdoor running, supporting the hypothesis. Variability was higher in the initial duration of running as compared to final phase of running. These findings suggest that treadmill may not fully reflect the dynamics of running over-ground. It is important to consider variability in gait analysis and research, as well as the potential impact on training and clinical practice.

Assessing the Accuracy of Smartwatch-Based Estimation of Maximum Oxygen Uptake Using the Apple Watch Series 7: Validation Study.

Determining maximum oxygen uptake (VO2max) is essential for evaluating cardiorespiratory fitness. While laboratory-based testing is considered the gold standard, sports watches or fitness trackers offer a convenient alternative. However, despite the high number of wrist-worn devices, there is a lack of scientific validation for VO2max estimation outside the laboratory setting. This study aims to compare the Apple Watch Series 7's performance against the gold standard in VO2max estimation and Apple's validation findings. A total of 19 participants (7 female and 12 male), aged 18 to 63 (mean 28.42, SD 11.43) years were included in the validation study. VO2max for all participants was determined in a controlled laboratory environment using a metabolic gas analyzer. Thereby, they completed a graded exercise test on a cycle ergometer until reaching subjective exhaustion. This value was then compared with the estimated VO2max value from the Apple Watch, which was calculated after wearing the watch for at least 2 consecutive days and measured directly after an outdoor running test. The measured VO2max (mean 45.88, SD 9.42 mL/kg/minute) in the laboratory setting was significantly higher than the predicted VO2max (mean 41.37, SD 6.5 mL/kg/minute) from the Apple Watch (t18=2.51; P=.01) with a medium effect size (Hedges g=0.53). The Bland-Altman analysis revealed a good overall agreement between both measurements. However, the intraclass correlation coefficient ICC(2,1)=0.47 (95% CI 0.06-0.75) indicated poor reliability. The mean absolute percentage error between the predicted and the actual VO2max was 15.79%, while the root mean square error was 8.85 mL/kg/minute. The analysis further revealed higher accuracy when focusing on participants with good fitness levels (mean absolute percentage error=14.59%; root-mean-square error=7.22 ml/kg/minute; ICC(2,1)=0.60 95% CI 0.09-0.87). Similar to other smartwatches, the Apple Watch also overestimates or underestimates the VO2max in individuals with poor or excellent fitness levels, respectively. Assessing the accuracy and reliability of the Apple Watch's VO2max estimation is crucial for determining its suitability as an alternative to laboratory testing. The findings of this study will apprise researchers, physical training professionals, and end users of wearable technology, thereby enhancing the knowledge base and practical application of such devices in assessing cardiorespiratory fitness parameters.

Clustering Runners' Response to Different Midsole Stack Heights: A Field Study.

Advanced footwear technology featuring stack heights higher than 30 mm has been proven to improve running economy in elite and recreational runners. While it is understood that the physiological benefit is highly individual, the individual biomechanical response to different stack heights remains unclear. Thirty-one runners performed running trials with three different shoe conditions of 25 mm, 35 mm, and 45 mm stack height on an outdoor running course wearing a STRYD sensor. The STRYD running variables for each participant were normalized to the 25 mm shoe condition and used to cluster participants into three distinct groups. Each cluster showed unique running patterns, with leg spring stiffness and vertical oscillation contributing most to the variance. No significant differences were found between clusters in terms of body height, body weight, leg length, and running speed. This study indicates that runners change running patterns individually when running with footwear featuring different stack heights. Clustering these patterns can help understand subgroups of runners and potentially support running shoe recommendations.

Air speed and direction affect metabolic and thermoregulatory responses during walking and running in a temperate environment.

Revisiting classical experiments on the impact of air resistance on metabolic rate, we aimed to overcome limitations of previous research, notably: low participant numbers (n = 1-3), highly turbulent wind, and confounding effects of rising body temperature. In a custom-built wind tunnel with reduced turbulence, 14 participants (8 males, 6 females) walked (5 km·h-1) and ran on a treadmill (70%V̇o2max) at 0, 2, 4, and 6 m·s-1 headwind or tailwind in a counterbalanced design, with rest breaks between each exposure to avoid rises in body core temperature. Oxygen consumption (V̇o2) exhibited strong linear relationships versus wind direction, dynamic pressure, and air speed squared (Vwr2), lower in magnitude for headwind than tailwind. A moderate linear relationship was observed between heart rate, wind direction, dynamic pressure, and Vwr2. Below 4 m·s-1, the effect of wind was well within inter- and intraindividual variation and equipment uncertainty, and only at wind speeds ≥4 m·s-1 did the differences in physiological responses reach statistical significance. Our data indicate that at running speeds below 4 m·s-1 (14.4 km/h), indoor treadmills and outdoor running are comparable in terms of the metabolic impact of air movement relative to the person. However, this does not extend to the thermoregulatory effect of wind, with outdoor running providing a higher cooling rate due to the self-generated wind created during running. By removing the confounding impact of core temperature rises, the observed effects of headwind were lower and those of tailwind larger than observed previously. In the context of middle-distance running, the headwind created by running at 21.5 km·h-1 would result in a 2.2% increase of V̇o2. A relative tailwind of the same speed would lead to a 3.1% reduction.NEW & NOTEWORTHY Revisiting classical work by Pugh and Davies on the metabolic effects of air speed and direction, shortcomings in the original studies were addressed. Using more participants, less turbulent wind, and avoiding confounding effects of work-induced core temperature increases, new equations describing the impact of air speed/direction were developed. This study observed a lower impact of headwind and a larger impact of tailwind in the absence of an exercise-induced core temperature increase.

Whole body sweat rate prediction: outdoor running and cycling exercise.

Our aim was to develop and validate separate whole body sweat rate prediction equations for moderate to high-intensity outdoor cycling and running, using simple measured or estimated activity and environmental inputs. Across two collection sites in Australia, 182 outdoor running trials and 158 outdoor cycling trials were completed at a wet-bulb globe temperature ranging from ∼15°C to ∼29°C, with ∼60-min whole body sweat rates measured in each trial. Data were randomly separated into model development (running: 120; cycling: 100 trials) and validation groups (running: 62; cycling: 58 trials), enabling proprietary prediction models to be developed and then validated. Running and cycling models were also developed and tested when locally measured environmental conditions were substituted with participants' subjective ratings for black globe temperature, wind speed, and humidity. The mean absolute error for predicted sweating rate was 0.03 and 0.02 L·h-1 for running and cycling models, respectively. The 95% confidence intervals for running (+0.44 and -0.38 L·h-1) and cycling (+0.45 and -0.42 L·h-1) were within acceptable limits for an equivalent change in total body mass over 3 h of ±2%. The individual variance in observed sweating described by the predictive models was 77% and 60% for running and cycling, respectively. Substituting measured environmental variables with subjective assessments of climatic characteristics reduced the variation in observed sweating described by the running model by up to ∼25%, but only by ∼2% for the cycling model. These prediction models are publicly accessible (https://sweatratecalculator.com) and can guide individualized hydration management in advance of outdoor running and cycling.NEW & NOTEWORTHY We report the development and validation of new proprietary whole body sweat rate prediction models for outdoor running and outdoor cycling using simple activity and environmental inputs. Separate sweat rate models were also developed and tested for situations where all four environmental parameters are not available, and some must be subsequently estimated by the user via a simple rating scale. All models are freely accessible through an online calculator: https://sweatratecalculator.com. These models, via the online calculator, will enable individualized hydration management for training or recreational cycling or running in an outdoor environment.

Transference of outdoor gait-training to treadmill running biomechanics and strength measures: A randomized controlled trial

Outdoor gait-training has been successful in improving pain and reducing contact time during outdoor running for runners with exercise-related lower leg pain (ERLLP). However, it is unclear if these adaptations translate to gold standard treadmill running and clinical strength assessments. The study purpose was to assess the influence of a 4-week outdoor gait-training intervention with home exercises (FBHE) on treadmill running biomechanics and lower extremity strength compared to home exercises alone (HE) among runners with ERLLP. Seventeen runners with ERLLP were randomly allocated to FBHE and HE groups (FBHE: 3 M, 6F, 23 ± 4 years, 22.0 ± 4.6 kg/m2; HE: 3 M, 5F, 25 ± 5 years, 24.0 ± 4.0 kg/m2). Both groups completed eight sessions of home exercises over 4 weeks. The FBHE group received gait-training through wearable sensors to reduce contact time. Treadmill running gait and clinical strength assessments were conducted at baseline and 4-weeks. Multivariate repeated measures analyses of variance were used to assess the influence of group and timepoint for all outcomes. The FBHE group demonstrated significantly decreased contact time at 4-weeks compared to baseline and the HE group (Mean Difference [MD] range: −42 ms – −39 ms; p-range: <0.001–0.02). The FBHE group had significantly increased cadence (MD: +21 steps/min; p = 0.003) and decreased loading impulse (MD: −51, p < 0.001) during treadmill running at 4-weeks compared to the HE group. Strength did not significantly differ adjusting for multiple comparisons (p > 0.007). The outdoor FBHE intervention transferred to favorable changes in treadmill running biomechanics. Clinicians treating runners with ERLLP patients should implement data-driven outdoor gait-training to maximize patient benefits across running locations.

Blood Morphological and Biochemical Indicator Characteristics in Men Performing Different Physical Activities in the Cold-A Preliminary Report.

This descriptive study determined whether winter swimming (WS) and outdoor amateur running (RUN) affect blood morphological and biochemical indicators in men during midseason winter swimming from November to April. There were three groups of participants, with 10 male amateurs each: RUN + WS, WS, and control. The research was performed in the middle of the winter swimming season of 2020/2021. This time period was chosen in consideration of the respondents' adaptation to winter conditions. The study involved only 10 male amateurs in each study group owing to COVID-19 pandemic restrictions, which confined people to their homes. In the RUN + WS group compared with the WS group, significant decreases in the mean corpuscular hemoglobin concentration (within standard limits) (p = 0.04) and platelet distribution width (p = 0.006) were observed, with a significant increase in the red blood cell distribution width (p = 0.008) (within standard limits). The renal function, as expressed by the estimated glomerular filtration rate, was higher in the RUN + WS group (p = 0.02) (within standard limits) compared with the WS group, and the uric acid concentration was reduced (p = 0.01). In the RUN + WS group compared with the control group, significant decreases in the leukocyte count (p = 0.02) (within standard limits), monocyte count (p = 0.04) (within standard limits), and platelet distribution width (p = 0.005) were reported. The remaining indicators presented a p-value > 0.05. The two investigated forms of physical activity had no negative effect on blood morphological or biochemical indicators in male amateurs during the winter swimming midseason.

Relationship Between Running Biomechanics and Core Temperature Across a Competitive Road Race.

Outdoor races introduce environmental stressors to runners, and core temperature changes may influence runners' movement patterns. This study assessed changes and determined relationships between sensor-derived running biomechanics and core temperature among runners across an 11.27-km road race. Core temperatures would increase significantly across the race, related to changes in spatiotemporal biomechanical measures. Cross-sectional cohort study. Level 3. Twenty runners (9 female, 11 male; age, 48 ± 12 years; height, 169.7 ± 9.1 cm; mass, 71.3 ± 13.4 kg) enrolled in the 2022 Falmouth Road Race were recruited. Participants used lightweight technologies (ingestible thermistors and wearable sensors) to monitor core temperature and running biomechanics throughout the race. Timestamps were used to align sensor-derived measures for 7 race segments. Observations were labeled as core temperatures generally within normal limits (<38°C) or at elevated core temperatures (≥38°C). Multivariate repeated measures analyses of variance were used to assess changes in sensor-derived measures across the race, with Bonferroni post hoc comparisons for significant findings. Pearson's r correlations were used to assess the relationship between running biomechanics and core temperature measures. Eighteen participants developed hyperthermic core temperatures (39.0°C ± 0.5°C); core temperatures increased significantly across the race (P < 0.01). Kinetic measures obtained from the accelerometers, including shock, impact, and braking g, all significantly increased across the race (P < 0.01); other sensor-derived biomechanical measures did not change significantly. Core temperatures were weakly associated with biomechanics (|r range|, 0.02-0.16). Core temperatures and kinetics increased significantly across a race, yet these outcomes were not strongly correlated. The observed kinetic changes may have been attributed to fatigue-related influences over the race. Clinicians may not expect changes in biomechanical movement patterns to signal thermal responses during outdoor running in a singular event.

Asymmetric running is associated with pain during outdoor running in individuals with Achilles tendinopathy in the return-to-sport phase

ObjectivesTo determine the relationships between (1) Achilles tendon pain and loading symmetry, and (2) number of running bouts and symptom severity, during two weeks of outdoor running in individuals with Achilles tendinopathy. DesignProspective, observational study. SettingBiomechanics laboratory and outdoors. ParticipantsSeventeen runners with Achilles tendinopathy in the return-to-sport phase of rehabilitation. Main outcome measuresSymptom severity was recorded with the Victorian Institute of Sports Assessment-Achilles (VISA-A) questionnaire. Running bouts and Achilles tendon pain during runs were recorded with daily training logs. Ground contact time was collected during runs with wearable sensors. Linear mixed modeling determined if the relationship between Achilles tendon pain and ground contact time symmetry during running was moderated by consecutive run days. Multiple regression determined the relationship between number of running bouts and change in VISA-A scores over two weeks, adjusted for run distance. ResultsGreater ground contact time on the contralateral leg corresponded to increased ipsilateral tendon pain for each consecutive run day (b = −0.028, p < 0.001). Number of running bouts was not associated with 2-week changes in VISA-A scores (p = 0.672). ConclusionsPain during running is associated with injured leg off-loading patterns, and this relationship strengthened with greater number of consecutive run days. Number of running bouts was not related to short-term symptom severity.

The Importance of Landscape during Long-Distance Running Activity

Outdoor running has a positive impact on human health. Our study attempted to address the issue of what other aspects motivate people to take up running. We were particularly interested in the landscape and its significance at the stage of decision making regarding participation in races. Our goal was also to identify the landscape features of routes, which determine their popularity. We conducted surveys among running participants and spatial analyses using GIS tools. Great landscape values of running routes can contribute to the activation of a running society, especially those including women and city dwellers. The high diversity of the landscape of cross-country routes, especially in terms of their relief and land use, significantly affects their high landscape rating. Route profiles and running challenges are as important as landscape values. The landscape that runners observe during long-distance runs affects their regeneration and motivates them to finish competitions. Runs organised in mountain and foothill landscapes, characterised by a wide variety of landscapes, are particularly attractive for runners. This study illuminates how the enchanting tapestry of landscapes not only fuels the passion for outdoor running but also underscores the intricate relationship between humans and their surroundings. The results enable us to establish the key principles for designing new running routes that support runners during their exertion.

Reliability of running parameters using fitness watches synced with accelerometers during outdoor runs

Background: To prevent running related injuries and return to sport activities, monitoring the running dynamic parameters (cadence, stride length, ground contact time and vertical oscillation) especially outdoor running is crucial. Previous studies investigated the reliability of these parameters in laboratory settings. However, the nature of outdoor runs is different (curve, uphill, other runners, etc.) and challenging in terms of equipment (simple) and environments (grass, asphalt, rubber, etc.). Therefore, the reliability of these parameters using a fitness watch synced with accelerometer needed to be investigated. Objective: To investigate the reliability of running parameters measured using fitness watches and accelerometers during outdoor runs. Materials and methods: 30 healthy volunteers (age 25.8±9.6 years, height 167.2±9.3 cm, weight 62.4±14.2 kg, and body mass index 22.2±3.8 kg/m2) participated in the study. They wore a fitness watch and attached a synced accelerometer at their pants. They completed 2 running laps (800 meters each) at their comfortable speeds. Resting periods were provided between laps. To control the speed for the second lap, the watch was set the maximum and minimum speed and set vibration and sound alarm mode. Running parameters include cadence, stride length, vertical oscillation, and ground contact time. Results: The reliability of the four running parameters (cadence, stride length, ground contact time, and vertical oscillation), indicated by the intraclass correlation coefficients (ICC (3,k)) was 0.94, 0.97, 0.98 and 0.99, respectively. Very high reliability values were confirmed. Conclusion: Using a fitness watch synced with an accelerometer during outdoor runs, running dynamic parameters (cadence, stride length, ground contact time, and vertical oscillation) illustrated very high levels of reliability.

Overheating and Air Velocities in Modern Office Buildings During Heating Season

Proper design and operation of buildings are expected to result in optimal thermal comfort and energy performance at the same time. If occupants are not satisfied with thermal conditions, corrective actions by building managers and maintenance staff may lead to elevated room temperatures with evident energy penalties. Because of complicated technical systems and control logic, it is worth studying how well the design intent has been realised in new office buildings. In this study, thermal comfort was analysed by measurements of draught, room, and supply air temperature as well as with occupant questionnaire surveys in five modern office buildings. Both short‐ and long‐term measurements were conducted to demonstrate problems in the operation and to find potential solutions for improvement. The results revealed an issue of excessive overheating during the heating season despite generally low air velocities. Radiant ceiling panels had the lowest velocities in both summer and winter, while buildings with active chilled beams showed the potential to meet Category II air velocity and temperature requirements. The building with thermally activated building systems experienced the most overheating during the heating season. Occupants were satisfied with the heating season temperatures of 23°C–25°C that can be attributed to lighter clothing (0.7 clo) instead of the standard 1.0 clo. Ventilation supply air and indoor temperature analyses indicate that elevated setpoints have been used to compensate for draught, resulting in overheating. As a measure of improvement to avoid overheating, we propose control curves for room temperature based on the outdoor running mean temperature and for supply air temperature based on the extract air temperature.

A Comparison of Critical Speed and Critical Power in Runners Using Stryd Running Power.

Although running traditionally relies on critical speed (CS) as an indicator of critical intensity, portable inertial measurement units offer a potential solution for estimating running mechanical power to assess critical power (CP) in runners. The purpose of this study was to determine whether CS and CP differ when assessed using the Stryd device, a portable inertial measurement unit, and if 2 running bouts are sufficient to determine CS and CP. On an outdoor running track, 10 trained runners (V˙O2max, 59.0 [4.2]mL·kg-1·min-1) performed 3 running time trials (TT) between 1200 and 4400m on separate days. CS and CP were derived from 2-parameter hyperbolic speed-time and power-time models, respectively, using 2 (CS2TT and CP2TT) and 3 (CS3TT and CP3TT) TTs. Subsequently, runners performed constant-intensity running for 800m at their calculated CS3TT and CP3TT. Running at the calculated CS3TT speed (3.88 [0.44]m·s-1) elicited an average Stryd running power (271 [28]W) not different from the calculated CP3TT (270 [28]; P = .940; d = 0.02), with excellent agreement between the 2 values (intraclass correlation coefficient = .980). The CS2TT (3.97 [0.42]m·s-1) was not higher than CS3TT (3.89 [0.44]m·s-1; P = .178; d = 0.46); however, CP2TT (278 [29] W) was greater than CP3TT (P = .041; d = 0.75). The running intensities at CS and CP were similar, supporting the use of running power (Stryd) as a metric of aerobic fitness and exercise prescription, and 2 trials provided a reasonable, albeit higher, estimate of CS and CP.

Biomechanics and subjective measures of recreational male runners in three shoes running outdoors: a randomised crossover study

We compared biomechanical and subjective data from outdoor running in: habitual (OWN), Saucony Endorphin Racer 2 minimal (FLAT) and Nike Vaporfly 4% (VP4) shoes. We also explored relationships between comfort measures and the collected data. Eighteen male recreational runners ran three 1.5-km trials outdoors, once per shoe. The first 1.1 km was run at a self-selected comfortable (slower) speed, and last 400 m at perceived 5-km race pace (faster). A GPS-enabled smartwatch, 15-m Optojump system, high-speed camera and tibial accelerometer collected biomechanical data. Subjective data on comfort, shoe properties and overall running experience were collected using visual analogue scales (VAS) and rankings. Cadence, leg stiffness and vertical stiffness were greater in FLAT than both OWN and VP4 at the slower speed (trivial to small ES). At both speeds, footstrike angles were smaller in FLAT (small to large ES), while propulsion phase was shorter in VP4 (moderate to large ES). FLAT was ranked as the least comfortable at the slower speed and most likely to cause injury, whereas OWN as the most comfortable and least likely to cause injury. Comfort was not significantly different at the faster speed between shoes. Comfort measures were more strongly correlated to subjective than biomechanical data. The two experimental shoes generally had non-significant or small effects on running biomechanics versus OWN. As VP4 are more like traditional than minimal shoes, these were perceived as more comfortable. Running speed appeared to affect subjective measures. Speed should be considered when prescribing and selecting shoes.

Biomechanical changes identified during a marathon race among high-school aged runners

BackgroundDespite the increasing popularity of endurance running competitions among adolescent runners, there is currently limited information regarding expected biomechanical changes across the duration of a long-distance running event, and the relationship between young runners’ biomechanics and running performance. Wearable technology offers an ecological means to continuously assess runners’ biomechanical data during outdoor running competitions. Research questionDo adolescent athletes adopt changes in sensor-derived biomechanics throughout a marathon race, and are there relationships between race performance and biomechanical features among young marathoners? MethodsFourteen high-school aged runners (9 M, 5 F; age: 16 ± 1 years, height: 170.8 ± 7.5 cm; mass: 63.6 ± 9.4 kg) wore lace-mounted sensors to record step-by-step biomechanics during a marathon race. Official race segment completion times were extracted across 5 race segments (5-K, 15-K, Half Marathon [21.1-K], 35-K, Marathon [42.2-K]). Within-participant repeated measures of covariance (pace) were conducted to assess changes in biomechanics across the race, with Bonferroni post-hoc comparisons. Pearson’s r correlations were performed to assess the relationship between race finish times and biomechanics. ResultsPace was significantly slower (p-range: 0.002–0.005), contact times significantly longer, and stride lengths significantly shorter in the final segment compared to middle segments (p-range: 0.003–0.004). The rate of shock accumulation was significantly higher in the final race segment compared to the first three segments (p-range: 0.001–0.002). Moderate relationships existed between finish times and pace (r = −0.63), stride length (r = −0.62), and contact time (r = 0.51). SignificanceAdolescent runners altered their gait patterns in the final marathon segment compared to earlier segments. Spatiotemporal measures were moderately correlated with race finish times, suggesting a link between faster run pace, increased stride lengths, and reduced contact time for improved running performance during an endurance race.

Navigating a sighted world: visually impaired runners’ experiences of the COVID-19 pandemic

During lockdown in March 2020, daily outdoor exercise was encouraged but little consideration was given to the feasibility of this for visually impaired (VI) people, for whom social distancing measures presented significant challenges. Drawing upon the concepts of ableism and ocularcentrism, this article explores VI peoples’ lived experiences of outdoor running (or not) during the COVID-19 pandemic. Eight VI runners participated in two semi-structured interviews during the pandemic. This longitudinal approach captured the impact of changing restrictions, personal circumstances, and seasons. Their running practices were shaped in complex and varied ways depending on impairment and impairment effects, local running environment, and support networks. Despite some commonalities, each personal story during this time was unique. Participants described empowering moments, juxtaposed with marginalising and oppressive situations. The UK Government’s encouragement of outdoor exercise was laden with ableist assumptions, and VI runners were significantly affected by the ocularcentric world they inhabit.

Prediction of instantaneous perceived effort during outdoor running using accelerometry and machine learning.

The rate of perceived effort (RPE) is a subjective scale widely used for defining training loads. However, the subjective nature of the metric might lead to an inaccurate representation of the imposed metabolic/mechanical exercise demands. Therefore, this study aimed to predict the rate of perceived exertions during running using biomechanical parameters extracted from a commercially available running smartwatch. Forty-three recreational runners performed a simulated 5-km race on a track, providing their RPE from a Borg scale (6-20) every 400 m. Running distance, heart rate, foot contact time, cadence, stride length, and vertical oscillation were extracted from a running smartwatch (Garmin 735XT). Machine learning regression models were trained to predict the RPE at every 5 s of the 5-km race using subject-independent (leave-one-out), as well as a subject-dependent regression method. The subject-dependent method was tested using 5%, 10%, or 20% of the runner's data in the training set while using the remaining data for testing. The average root-mean-square error (RMSE) in predicting the RPE using the subject-independent method was 1.8 ± 0.8 RPE points (range 0.6-4.1; relative RMSE ~ 12 ± 6%) across the entire 5-km race. However, the error from subject-dependent models was reduced to 1.00 ± 0.31, 0.66 ± 0.20 and 0.45 ± 0.13 RPE points when using 5%, 10%, and 20% of data for training, respectively (average relative RMSE < 7%). All types of predictions underestimated the maximal RPE in ~ 1 RPE point. These results suggest that the data accessible from commercial smartwatches can be used to predict perceived exertion, opening new venues to improve training workload monitoring.

Study on adaptive thermal comfort model and behavioral adaptation in naturally ventilated residential buildings, Jimma Town, Ethiopia

Ethiopia boasts abundant untapped energy resources, yet access to electricity remains limited (30%), with frequent and prolonged outages. Research on occupant thermal comfort in Ethiopia remains limited as well. This study aimed to investigate comfort temperature, adaptive models, and behavioral adaptations in naturally ventilated residential buildings in Jimma town, Ethiopia. Our thermal comfort field survey involved 870 occupants from 104 houses, generating 5220 datasets between February and September 2020. Indoor environments were simultaneously measured using handheld digital instruments. Notably, the subjects lacked electrical fans, space heaters, or air-conditioners, relying instead on charcoal and plant residue for cooking and heating.Overall, only 56.2% of subjects felt comfortable within the thermal sensation scale's defined band, while 70.9% preferred either warmer or cooler environments, and 63.4% accepted their environments. The mean comfort temperature was 23.3˚C ± 3.44 based on all data. Our adaptive model predicted a 1.82 K perturbation in outdoor running mean temperature, resulting in a unit change in indoor comfort temperature. Significant occupant behavioral adaptation through operable environmental controls, clothing choices, and activity levels was observed. Our model is essential for building simulation in Ethiopia, emphasizing the need for an Ethiopian adaptive standard. Given the limited modern energy sources, understanding low-energy thermal comfort and human adaptation becomes vital for sustainable living conditions.