TECO Wearable Framework (TWS)

The TECO Wearable Framework (TWS) is a comprehensive collection of electronic modules, components, materials, embedded software and applications (for user interfaces and data analytics) used in TECO’s wearable research projects. It builds on around 20 years of student and PhD work at TECO, assembling prior modules into a coherent framework. The framework supports rapid prototyping of wearable systems—for example haptic displays, sensor modules, soft-electronics and materials suitable for wearables.

Provide a modular, reusable infrastructure (hardware + software + materials) to speed up the creation of wearable systems for research and teaching. Support rapid prototyping of haptic displays, wearable sensor modules, flexible electronics and new human-wearable user interfaces. Enable bridging of multiple domains (user interface design, embedded systems, wearable sensors/actuators, data analytics) in a cohesive platform.

Haptic Displays & Actuators: Includes modules like the “VibrationCap” (vibration motors for head/neck/hand), the “RüttelFlug” framework (haptics for the arm, used in sports applications) and the “ProximityHat” framework (pressure-sensation wearable). Sensor Frameworks: Includes the “AURA” framework (medical sensor wearable for head-based attachment, with sensors for breathing, ECG/EEG/EMG, SpO₂), the “Earables” framework (wearable sensors embedded in or on the ear), and the “bPart” series (tiny BLE sensor modules embedded in clothing/objects). Wearable UI & Materials: Such as “SecondSkin” (TPU/PDMS-based flexible printed circuits for skin-like attachments), and “AR-Sensors” (augmented-reality data overlays for wearables). The framework enables constructing new wearables within a week in many cases via modular hardware/software building blocks.

By providing a reusable framework, TWS accelerates wearable technology research at TECO and beyond, lowering the barrier for prototyping novel wearable devices. Supports cross-disciplinary projects (wearable hardware, user interaction, data analytics), which fosters innovations in human-computing, health wearables, sports technologies, ambient-intelligence wearables. The modular nature means that research and student projects can iterate faster, share components and build on older modules rather than starting from scratch each time. Potentially contributes to more wearable systems reaching real-world use (in health, sports, ambient assistance) due to shortened development cycles and well-tested building blocks.