Wearable Sensing

Wearable Inertial Measurement Units (IMU) measuring acceleration, earth magnetic field and gyroscopic measurements can be considered for capturing human skeletal postures in real time. This dataset contains IMU readings (accelerometer, magnetometer and gyroscope) for common shoulder exercises: extension- flexion and abduction-adduction and simultaneously measures VICON readings and Kinect readings.

  • Wearable Sensing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Pubudu N. Pathirana, M. Sajeewani Karunarathne, Gareth L. Williams, Phan T. Nam, Hugh Durrant-Whyte

    Orientation tracking of a moving object has a widevariety of applications, including but not limited to military,surgical aid, navigation systems, mobile robots, gaming, virtualreality, and gesture recognition. In this article, a novel algorithmis presented to automatically track and quantify change ofdirection (COD) incident angles or heading angles (i.e. turningangles) of a moving athlete using the inertial sensor signals froma microtechnology unit (an inertia measurement unit (IMU))commonly used in elite sport.

  • Sensors
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Mahir Meghji,Aaron Balloch,Daryoush Habibi,Iftekhar Ahmad,Nicolas Hart,Robert Newton,Jason Weber,Adnan Waqar

    This dataset is a highly versatile and precisely annotated large-scale dataset of smartphone sensor data for multimodal locomotion and transportation analytics of mobile users.

    The dataset comprises 7 months of measurements, collected from all sensors of 4 smartphones carried at typical body locations, including the images of a body-worn camera, while 3 participants used 8 different modes of transportation in the southeast of the United Kingdom, including in London.

  • Computational Intelligence
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Hristijan Gjoreski, Mathias Ciliberto, Lin Wang, Francisco Javier Ordoñez Morales, Sami Mekki, Stefan Valentin, Daniel Roggen

    This dataset consists of raw EEG data from 48 subjects who participated in a multitasking workload experiment utilizing the SIMKAP multitasking test. The subjects’ brain activity at rest was also recorded before the test and is included as well. The Emotiv EPOC device, with sampling frequency of 128Hz and 14 channels was used to obtain the data, with 2.5 minutes of EEG recording for each case. Subjects were also asked to rate their perceived mental workload after each stage on a rating scale of 1 to 9 and the ratings are provided in a separate file.

  • Biophysiological Signals
  • Last Updated On: 
    Tue, 07/10/2018 - 02:19

    The electronic system has been design to know the position human body. Of this way the system use a three axis accelerometer to detect five common positions (i) ventral decubitus, (ii) right lateral decubitus, (iii) left lateral decubitus, (iv) supine decubitus and (v) seated.  The sensor data was acquire with ten diferrents persons, their each positions was  how they felt confortable. The accelerometer acquire data from  3 axis possible (X,Y,Z)

  • Health
  • Last Updated On: 
    Sat, 06/16/2018 - 22:57

    Expansion of wireless body area networks (WBANs) applications such as health-care, m-banking, and others  has lead to vulnerability of privacy and personal data. An effective and unobtrusive natural method of authentication is therefore a necessity in such applications. Accelerometer-based gait recognition has become an attractive solution, however, continuous sampling of accelerometer data reduces the battery life of wearables. This paper investigates the usage of received signal strength indicator (RSSI) as a source of gait recognition.

  • Communications
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Marshed Mohamed and Michael Cheffena

    Previous neuroimaging research has been traditionally confined to strict laboratory environments due to the limits of technology. Only recently have more studies emerged exploring the use of mobile brain imaging outside the laboratory. This study uses electroencephalography (EEG) and signal processing techniques to provide new opportunities for studying mobile subjects moving outside of the laboratory and in real world settings. The purpose of this study was to document the current viability of using high density EEG for mobile brain imaging both indoors and outdoors.

  • Neuroscience
  • Last Updated On: 
    Sat, 06/16/2018 - 23:16

    The impact of high curvature bending on thin film transistor(TFT) performance is of interest for flexible electronics. Bending influences TFT performance in two ways. First due to mechanical stress and second due to the pure geometric effect of converting a planar architecture to a cylindrical one. Experiments to simultaneously create and yet distinguish these two effects are difficult. Analytical models are required to identify the individual impact of stress and geometry. The goal of this work is to identify the purely geometrical impact on TFT characteristics.

  • Sensors
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Prasenjit Bhattacharya, Aswathi Nair, Sanjiv Sambandan

    The image displays four segments of gestures from our dataset.

    (a) The video sequence of rotating the wrist down and up as a signal for starting a new gesture.

    (b)–(d) Three gestures samples (the triangle, letter b, and letter Z) taken from three different subjects at three different scenes (sitting at a desk, standing indoors, and standing outdoors.). The trajectory of each gesture canbe recognized from the movement of the background objects.

  • Wearable Sensing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Feiyu Chen, Honghao Lv, Zhibo Pang, Junhui Zhang, Huayong Yang, Geng Yang*

      In recent years, researchers have explored gesture-based interfaces to control robots in non-traditional ways. These interfaces require the ability to track the body movements of the user in 3D. Deploying mo-cap systems for tracking tends to be costly, intrusive, and requires a clear line of sight, making them ill-adapted for applications that need fast deployment, such as artistic performance and emergency response.

  • Wearable Sensing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    David St-Onge and Ulysse Côté-Allard and Giovanni Beltrame

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