Robust single finger movement detection scheme for real time wheelchair control by physically challenged people

Author(s):  
Sayeed Shafayet Chowdhury ◽  
Rakib Hyder ◽  
Celia Shahanaz ◽  
Shaikh Anowarul Fattah
Author(s):  
Wenqiang Chen ◽  
Lin Chen ◽  
Meiyi Ma ◽  
Farshid Salemi Parizi ◽  
Shwetak Patel ◽  
...  

Wearable devices, such as smartwatches and head-mounted devices (HMD), demand new input devices for a natural, subtle, and easy-to-use way to input commands and text. In this paper, we propose and investigate ViFin, a new technique for input commands and text entry, which harness finger movement induced vibration to track continuous micro finger-level writing with a commodity smartwatch. Inspired by the recurrent neural aligner and transfer learning, ViFin recognizes continuous finger writing, works across different users, and achieves an accuracy of 90% and 91% for recognizing numbers and letters, respectively. We quantify our approach's accuracy through real-time system experiments in different arm positions, writing speeds, and smartwatch position displacements. Finally, a real-time writing system and two user studies on real-world tasks are implemented and assessed.


2019 ◽  
Vol 19 (19) ◽  
pp. 12477-12494 ◽  
Author(s):  
Armin Sigmund ◽  
Korbinian Freier ◽  
Till Rehm ◽  
Ludwig Ries ◽  
Christian Schunk ◽  
...  

Abstract. To assist atmospheric monitoring at high-alpine sites, a statistical approach for distinguishing between the dominant air masses was developed. This approach was based on a principal component analysis using five gas-phase and two meteorological variables. The analysis focused on the Schneefernerhaus site at Zugspitze Mountain, Germany. The investigated year was divided into 2-month periods, for which the analysis was repeated. Using the 33.3 % and 66.6 % percentiles of the first two principal components, nine air mass regimes were defined. These regimes were interpreted with respect to vertical transport and assigned to the BL (recent contact with the boundary layer), UFT/SIN (undisturbed free troposphere or stratospheric intrusion), and HYBRID (influences of both the boundary layer and the free troposphere or ambiguous) air mass classes. The input data were available for 78 % of the investigated year. BL accounted for 31 % of the cases with similar frequencies in all seasons. UFT/SIN comprised 14 % of the cases but was not found from April to July. HYBRID (55 %) mostly exhibited intermediate characteristics, whereby 17 % of the HYBRID class suggested an influence from the marine boundary layer or the lower free troposphere. The statistical approach was compared to a mechanistic approach using the ceilometer-based mixing layer height from a nearby valley site and a detection scheme for thermally induced mountain winds. Due to data gaps, only 25 % of the cases could be classified using the mechanistic approach. Both approaches agreed well, except in the rare cases of thermally induced uplift. The statistical approach is a promising step towards a real-time classification of air masses. Future work is necessary to assess the uncertainty arising from the standardization of real-time data.


2015 ◽  
Vol 11 (11) ◽  
pp. 356382 ◽  
Author(s):  
Li Lu ◽  
Muhammad Jawad Hussain ◽  
Guoxing Luo ◽  
Zhigang Han
Keyword(s):  

BIOspektrum ◽  
2020 ◽  
Vol 26 (6) ◽  
pp. 624-627
Author(s):  
Ole Behrmann ◽  
Iris Bachmann ◽  
Frank Hufert ◽  
Gregory Dame

Abstract The COVID-19 pandemic highlights the need for fast and simple assays for nucleic acid detection. As an isothermal alternative to RT-qPCR, we outline the development of a detection scheme for SARS-CoV-2 RNA based on reverse transcription recombinase polymerase amplification (RT-RPA) technology. RPA uses recombination proteins in combination with a DNA polymerase for rapid amplification of target DNA at a constant temperature (39–42 °C) within 10 to 20 minutes and can be monitored in real-time with fluorescent probes.


2019 ◽  
Vol 15 (7) ◽  
pp. 4285-4294 ◽  
Author(s):  
Zhihong Tian ◽  
Wei Shi ◽  
Yuhang Wang ◽  
Chunsheng Zhu ◽  
Xiaojiang Du ◽  
...  

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