Smart Sportswear
Smart Sportswear - Related Videos
08:35
Are You Smart or Hardworking? How Praise Influences Children's Motivation
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2023
Source: Laboratories of Judith Danovitch and Nicholaus Noles—University of Louisville Imagine teaching two children how to skate. It is a hard task for both of them, and they fall down frequently. After falling down for the first time, one child says that skating is too hard and wants to go home. The other child seems to enjoy the challenge and eagerly gets back up after falling down each time. Why do the children have such different attitudes about the same task? One reason may be that they...
08:35
Hybrid Printing for the Fabrication of Smart Sensors
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Cited by 4 •
2019
Here we present a protocol for the fabrication of inkjet-printed multilayer sensor structures on additively manufactured substrates and foil.
07:47
Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
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Cited by 9 •
2018
This study presents a protocol of designing and manufacturing a glasses-type wearable device that detects the patterns of food intake and other featured physical activities using load cells inserted in both hinges of the glasses.
07:52
Cryo-Electron Microscopy Screening Automation Across Multiple Grids Using Smart Leginon
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Cited by 3 •
2023
Cryo-electron microscopy (cryoEM) multi-grid screening is often a tedious process that demands hours of attention. This protocol shows how to set up a standard Leginon collection and Smart Leginon Autoscreen to automate this process. This protocol can be applied to the majority of cryoEM holey foil grids.
10:30
Mesenchymal Stromal Cell Culture and Delivery in Autologous Conditions: A Smart Approach for Orthopedic Applications
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Cited by 28 •
2016
Culturing human Mesenchymal Stromal Cells (hMSCs) with autologous serum, reduces the risks of rejection by xenogeneic material and other negative effects. It also allows for the recovery of a subset of mesodermal progenitors, which can deliver fresh hMSCs. Embedding hMSCs in an autologous fibrin clot enables easy handling and effective surgical implantation.
FAQs
Conductive textiles provide pathways for electrical signals within clothing or athletic equipment, while miniature sensors detect movement, physiological signals, or surrounding conditions. A wireless communication system then transfers the collected measurements to a mobile device or analytical platform. This integration allows data collection during activity without requiring the participant to remain in a laboratory setting.
Depending on the embedded sensors, the system can record motion patterns, heart rate, temperature, and exertion. These measurements represent different aspects of activity: movement describes physical behavior, physiological signals indicate bodily response, and temperature or related environmental data adds context. Combining them supports a more complete interpretation of exercise habits and training responses.
Real-time feedback helps users recognize their current physical activity and modify it while the activity is occurring. By connecting collected measurements with immediate information, the system can make otherwise difficult-to-notice patterns more apparent. In behavioral research, this supports interventions designed to encourage changes in exercise habits rather than relying only on later recall or laboratory observation.
Measurements collected during everyday exercise provide continuous, ecologically relevant information about activity habits and patterns. This context can reveal how people actually train, respond, or maintain activity beyond controlled laboratory sessions. Smart sportswear therefore helps researchers examine behavior in natural settings while also tracking training responses and exertion across ongoing physical activity.
A typical workflow begins with wearing the sensor-equipped clothing or equipment during physical activity. Embedded components collect movement, physiological, or environmental measurements, and wireless communication sends the data to a mobile device or analytical platform. Researchers or users then interpret the resulting information to evaluate exercise habits, training responses, exertion, or activity patterns.
Researchers may choose this approach when they need continuous information about exercise behavior beyond the laboratory. It is especially relevant for studying activity patterns, training responses, and exercise habits as they occur in real settings. The technology can also support behavior-change interventions by providing feedback that connects observed activity with opportunities for adjustment.
The collected data can help identify movement patterns, physiological responses, temperature, or exertion relevant to physical activity. Interpreting these signals may support performance optimization, injury-prevention efforts, and rehabilitation monitoring. In behavior-focused applications, the same information can help users or practitioners recognize activity patterns and guide modifications during training or recovery.