Wii Remote | EPFL Graph Search

Are you an EPFL student looking for a semester project?

Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.

The Wii Remote, also known colloquially as the Wiimote, is the primary game controller for Nintendo's Wii home video game console. An essential capability of the Wii Remote is its motion sensing capability, which allows the user to interact with and manipulate items on screen via motion sensing, gesture recognition, and pointing which is used for the console, using accelerometer and technology. It is expandable by adding attachments. The attachment bundled with the Wii console is the Nunchuk, which complements the Wii Remote by providing functions similar to those in gamepad controllers. Some other attachments include the Classic Controller, Wii Zapper, and the Wii Wheel, which has originally been used for the racing game, Mario Kart Wii. The controller was revealed at both E3 2005 and E3 2006 and the Tokyo Game Show on September 14, 2005, with the name "Wii Remote" announced April 27, 2006. It received much attention due to its unique features, not supported by other gaming contro

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (6)

Related publications

Related people

Related units

Related concepts (21)

Related concepts

Related courses (1)

Related courses

Related lectures (1)

Related lectures

Embedded ultra-low power driver for a 7.2g helicopter and IrDA remote control

Patrick Clerc

In a previous project, a 7.2g helicopter made of carbon was designed and realized at the LAI. The goal of this project is to design and realize a tiny receiver and a remote capable of driving the helicopter from a distance of 2 to 4 meters. Challenges are here to make the receiver small and light enough to be embedded in the helicopter without disturbing the flight. Ultra-low consumption is also required. Both emitter and receiver will have to be designed and mounted by the student. The microcontroller is to be chosen in the MSP430F21x2 family. Well-known for their low-power consumption, they also possess an IrDA serial communication interface which will be used for a bi-directional communication between the helicopter and the remote. The remote will have to control 3 channels (lift, yaw and eventually pitch) and display the battery level of the helicopter.

2011

Real-world gait speed estimation using wrist sensor: A personalized approach

Kamiar Aminian, Hooman Dejnabadi, Martin Savary, Abolfazl Soltani

Gait speed is an important parameter to characterize people's daily mobility. For real-world speed measurement, inertial sensors or Global Navigation Satellite System (GNSS) can be used on wrist, possibly integrated in a wristwatch. However, power consumption of GNSS is high and data are only available outdoor. Gait speed estimation using wrist-mounted inertial sensors is generally based on machine learning and suffers from low accuracy due to the inadequacy of using limited training data to build a general speed model that would be accurate for the whole population. To overcome this issue, a personalized model was proposed, which took unique gait style of each subject into account. Cadence and other biomechanically-derived gait features were extracted from wrist-mounted accelerometer and barometer. Gait features were fused with few GNSS data (sporadically sampled during gait) to calibrate the step length model of each subject through online learning. The proposed method was validated on 30 healthy subjects. For walking, it has achieved a median [Interquartile Range] RMSE, bias and precision of 0.05 [0.04-0.06], 0.00 [-0.01 0.00], and 0.06 [0.05 0.07] (m/s), respectively. For running, the errors are 0.14 [0.11 0.17], 0.00 [-0.01 0.02], and 0.18 [0.14 0.23] (m/s), respectively. Results demonstrated that the personalized model provided similar performance as GNSS. It used 50 times less training GNSS data than non-personalized method and achieved even better results. This parsimonious GNSS usage allowed extending battery life. The proposed algorithm met requirements for applications which need accurate, long, real-time, low-power, and indoor/outdoor speed estimation in daily life.

2019

A wrist sensor and algorithm to determine instantaneous walking cadence and speed in daily life walking

Kamiar Aminian, Flavien Bardyn, Farzin Dadashi, Cyntia Duc, Pierre-André Farine, Benedikt Fasel, Martin Savary

In daily life, a person’s gait—an important marker for his/her health status—is usually assessed using inertial sensors fixed to lower limbs or trunk. Such sensor locations are not well suited for continuous and long duration measurements. A better location would be the wrist but with the drawback of the presence of perturbative movements independent of walking. The aim of this study was to devise and validate an algorithm able to accurately estimate walking cadence and speed for daily life walking in various environments based on acceleration measured at the wrist. To this end, a cadence likelihood measure was designed, automatically filtering out perturbative movements and amplifying the periodic wrist movement characteristic of walking. Speed was estimated using a piecewise linear model. The algorithm was validated for outdoor walking in various and challenging environments (e.g., trail, uphill, downhill). Cadence and speed were successfully estimated for all conditions. Overall median (interquartile range) relative errors were −0.13% (−1.72 2.04%) for instantaneous cadence and −0.67% (−6.52 6.23%) for instantaneous speed. The performance was comparable to existing algorithms for trunk- or lower limb-fixed sensors. The algorithm’s low complexity would also allow a real-time implementation in a watch.

Springer Heidelberg2017

ENV-548: Sensor orientation

Determination of spatial orientation (i.e. position, velocity, attitude) via integration of inertial sensors with satellite positioning. Prerequisite for many applications related to remote sensing, environmental monitoring, mobile mapping, robotics, space exploration, smart-phone navigation, etc.

Game controller

A game controller, gaming controller, or simply controller, is an input device or input/output device used with video games or entertainment systems to provide input to a video game. Input devices th

Nintendo Switch

The Nintendo Switch is a video game console developed by Nintendo and released worldwide in most regions on March 3, 2017. The console itself is a tablet that can either be docked for home console

Kinect

Kinect is a line of motion sensing input devices produced by Microsoft and first released in 2010. The devices generally contain RGB cameras, and infrared projectors and detectors that map depth throu