GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Wearables to Fight COVID-19: From Symptom Tracking to Contact Tracing
    Institute of Electrical and Electronics Engineers (IEEE) ; 2020
    In:  IEEE Pervasive Computing Vol. 19, No. 4 ( 2020-10-1), p. 53-60
    Details
    In: IEEE Pervasive Computing, Institute of Electrical and Electronics Engineers (IEEE), Vol. 19, No. 4 ( 2020-10-1), p. 53-60
    Type of Medium: Online Resource
    ISSN: 1536-1268 , 1558-2590
    URL: Article
    DOI: 10.1109/MPRV.2020.3021321
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2020
    detail.hit.zdb_id: 2077823-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    The State-of-the-Art Sensing Techniques in Human Activity Recognition: A Survey
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 12 ( 2022-06-17), p. 4596-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 12 ( 2022-06-17), p. 4596-
    Abstract: Human activity recognition (HAR) has become an intensive research topic in the past decade because of the pervasive user scenarios and the overwhelming development of advanced algorithms and novel sensing approaches. Previous HAR-related sensing surveys were primarily focused on either a specific branch such as wearable sensing and video-based sensing or a full-stack presentation of both sensing and data processing techniques, resulting in weak focus on HAR-related sensing techniques. This work tries to present a thorough, in-depth survey on the state-of-the-art sensing modalities in HAR tasks to supply a solid understanding of the variant sensing principles for younger researchers of the community. First, we categorized the HAR-related sensing modalities into five classes: mechanical kinematic sensing, field-based sensing, wave-based sensing, physiological sensing, and hybrid/others. Specific sensing modalities are then presented in each category, and a thorough description of the sensing tricks and the latest related works were given. We also discussed the strengths and weaknesses of each modality across the categorization so that newcomers could have a better overview of the characteristics of each sensing modality for HAR tasks and choose the proper approaches for their specific application. Finally, we summarized the presented sensing techniques with a comparison concerning selected performance metrics and proposed a few outlooks on the future sensing techniques used for HAR tasks.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22124596
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2052857-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    MoCaPose : Motion Capturing with Textile-integrated Capacitive Sensors in Loose-fitting Smart Garments
    Association for Computing Machinery (ACM) ; 2022
    In:  Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Vol. 7, No. 1 ( 2022-03-27), p. 1-40
    Details
    In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Association for Computing Machinery (ACM), Vol. 7, No. 1 ( 2022-03-27), p. 1-40
    Abstract: We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously track the wearer's upper body's dynamic poses through multi-channel capacitive sensing integrated in fashionable, loose-fitting jackets. Unlike conventional wearable IMU MoCap based on inverse dynamics, MoCaPose decouples the sensor position from the pose system. MoCaPose uses a deep regressor to continuously predict the 3D upper body joints coordinates from 16-channel textile capacitive sensors, unbound by specific applications. The concept is implemented through two prototyping iterations to first solve the technical challenges, then establish the textile integration through fashion-technology co-design towards a design-centric smart garment. A 38-hour dataset of synchronized video and capacitive data from 21 participants was recorded for validation. The motion tracking result was validated on multiple levels from statistics (R2 ~ 0.91) and motion tracking metrics (MP JPE ~ 86mm) to the usability in pose and motion recognition (0.9 F1 for 10-class classification with unsupervised class discovery). The design guidelines impose few technical constraints, allowing the wearable system to be design-centric and usecase-specific. Overall, MoCaPose demonstrates that textile-based capacitive sensing with its unique advantages, can be a promising alternative for wearable motion tracking and other relevant wearable motion recognition applications.
    Type of Medium: Online Resource
    ISSN: 2474-9567
    URL: Article
    DOI: 10.1145/3580883
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2022
    detail.hit.zdb_id: 2892727-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Induced Magnetic Field-Based Indoor Positioning System for Underwater Environments
    MDPI AG ; 2021
    In:  Sensors Vol. 21, No. 6 ( 2021-03-22), p. 2218-
    Details
    In: Sensors, MDPI AG, Vol. 21, No. 6 ( 2021-03-22), p. 2218-
    Abstract: Autonomous underwater vehicles (AUV) are seen as an emerging technology for maritime exploration but are still restricted by the availability of short range, accurate positioning methods necessary, e.g., when docking remote assets. Typical techniques used for high-accuracy positioning in indoor use case scenarios, such as systems using ultra-wide band radio signals (UWB), cannot be applied for underwater positioning because of the quick absorption of the positioning medium caused by the water. Acoustic and optic solutions for underwater positioning also face known problems, such as the multi-path effects, high propagation delay (acoustics), and environmental dependency. This paper presents an oscillating magnetic field-based indoor and underwater positioning system. Unlike those radio wave-based positioning modalities, the magnetic approach generates a bubble-formed magnetic field that will not be deformed by the environmental variation because of the very similar permeability of water and air. The proposed system achieves an underwater positioning mean accuracy of 13.3 cm in 2D and 19.0 cm in 3D with the multi-lateration positioning method and concludes the potential of the magnetic field-based positioning technique for underwater applications. A similar accuracy was also achieved for various indoor environments that were used to test the influence of cluttered environment and of cross environment. The low cost and power consumption system is scalable for extensive coverage area and could plug-and-play without pre-calibration.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s21062218
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2052857-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Social Distance Monitor with a Wearable Magnetic Field Proximity Sensor
    MDPI AG ; 2020
    In:  Sensors Vol. 20, No. 18 ( 2020-09-07), p. 5101-
    Details
    In: Sensors, MDPI AG, Vol. 20, No. 18 ( 2020-09-07), p. 5101-
    Abstract: Social distancing and contact/exposure tracing are accepted to be critical strategies in the fight against the COVID-19 epidemic. They are both closely connected to the ability to reliably establish the degree of proximity between people in real-world environments. We proposed, implemented, and evaluated a wearable proximity sensing system based on an oscillating magnetic field that overcomes many of the weaknesses of the current state of the art Bluetooth based proximity detection. In this paper, we first described the underlying physical principle, proposed a protocol for the identification and coordination of the transmitter (which is compatible with the current smartphone-based exposure tracing protocols). Subsequently, the system architecture and implementation were described, finally an elaborate characterization and evaluation of the performance (both in systematic lab experiments and in real-world settings) were performed. Our work demonstrated that the proposed system is much more reliable than the widely-used Bluetooth-based approach, particularly when it comes to distinguishing between distances above and below the 2.0 m threshold due to the magnetic field’s physical properties.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s20185101
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2052857-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 6
    Online Resource
    Online Resource
    Using Privacy Respecting Sound Analysis to Improve Bluetooth Based Proximity Detection for COVID-19 Exposure Tracing and Social Distancing
    MDPI AG ; 2021
    In:  Sensors Vol. 21, No. 16 ( 2021-08-20), p. 5604-
    Details
    In: Sensors, MDPI AG, Vol. 21, No. 16 ( 2021-08-20), p. 5604-
    Abstract: We propose to use ambient sound as a privacy-aware source of information for COVID-19-related social distance monitoring and contact tracing. The aim is to complement currently dominant Bluetooth Low Energy Received Signal Strength Indicator (BLE RSSI) approaches. These often struggle with the complexity of Radio Frequency (RF) signal attenuation, which is strongly influenced by specific surrounding characteristics. This in turn renders the relationship between signal strength and the distance between transmitter and receiver highly non-deterministic. We analyze spatio-temporal variations in what we call “ambient sound fingerprints”. We leverage the fact that ambient sound received by a mobile device is a superposition of sounds from sources at many different locations in the environment. Such a superposition is determined by the relative position of those sources with respect to the receiver. We present a method for using the above general idea to classify proximity between pairs of users based on Kullback–Leibler distance between sound intensity histograms. The method is based on intensity analysis only, and does not require the collection of any privacy sensitive signals. Further, we show how this information can be fused with BLE RSSI features using adaptive weighted voting. We also take into account that sound is not available in all windows. Our approach is evaluated in elaborate experiments in real-world settings. The results show that both Bluetooth and sound can be used to differentiate users within and out of critical distance (1.5 m) with high accuracies of 77% and 80% respectively. Their fusion, however, improves this to 86%, making evident the merit of augmenting BLE RSSI with sound. We conclude by discussing strengths and limitations of our approach and highlighting directions for future work.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s21165604
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2052857-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...