SoundWrite II: Ambient Acoustic Sensing for Noise Tolerant Device-Free Gesture Recognition

Luo, Gan; Chen, Mingshi; Li, Ping; Zhang, Maotian; Yang, Panlong

doi:10.1109/icpads.2017.00027

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…However, OFDM is mainly manifested in the CSI signal as introduced in Subsection 2. SoundSense [73] BodyScope [74] EarSense [75] HearFit [76] Liang and Thomaz [77] DopLink [79] Dolphin [80] SoundWrite [83] LLAP [84] VSkin [81] Vernier [82] UltraGesture [85] RobuCIR [86] Acousticcardiogram [89] Localization and Navigation…”

Section: Orthogonal Frequency Division Multiplexing (Ofdm)mentioning

confidence: 99%

“…Strata [135] estimates the channel impulse effect (CIR) in order to explicitly account for multipath propagation, and to select well-behaved channels and extract the phase change in the selected channel signal to accurately estimate the distance change of the finger, and uses a new optimization framework to estimate the absolute distance of the finger according to the change in CIR. The core work of Vernier [82] is calculated with a small signal window phase transition, whose number of local maxima corresponds to the number of cycles of the phase transition, removes complex frequency analysis and long windows of signal accumulation, and significantly reduces tracking delay and overhead. The evaluated results show that its tracking error is less than 4 mm, and the speed is also faster.…”

Section: ) Acoustic: Finger and Hand Motion Tracking Based On Acousticmentioning

confidence: 99%

“…After obtaining the WiFi or acoustic signal, the next step is to characterize it using various sensing techniques. Similar to WiFi sensing, typical applications based on acoustic sensing include daily actions monitoring [73][74][75][76][77][78] , gesture and hand movements recognition [79][80][81][82][83][84][85][86][87] , health caring [88][89][90][91][92] , localization and navigation [93][94][95][96][97][98] and privacy and security [99][100][101][102][103][104][105][106][107][108][109][110][111] . In the following, we will also introduce the basic content of signals and other characterization methods.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Huang

Wang

Zou

et al. 2023

J. Comput. Sci. Technol.

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With the increasing pervasiveness of mobile devices such as smartphones, smart TVs, and wearables, smart sensing, transforming the physical world into digital information based on various sensing medias, has drawn researchers' great attention. Among different sensing medias, WiFi and acoustic signals stand out due to their ubiquity and zero hardware cost. Based on different basic principles, researchers have proposed different technologies for sensing applications with WiFi and acoustic signals covering human activity recognition, motion tracking, indoor localization, health monitoring, and the like. To enable readers to get a comprehensive understanding of ubiquitous wireless sensing, we conduct a survey of existing work to introduce their underlying principles, proposed technologies, and practical applications. Besides we also discuss some open issues of this research area. Our survey reals that as a promising research direction, WiFi and acoustic sensing technologies can bring about fancy applications, but still have limitations in hardware restriction, robustness, and applicability.

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Section: Orthogonal Frequency Division Multiplexing (Ofdm)mentioning

confidence: 99%

Section: ) Acoustic: Finger and Hand Motion Tracking Based On Acousticmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Huang

Wang

Zou

et al. 2023

J. Comput. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Neither of the two methods can be used when the environment is noisy, primarily when the blasting sound is produced when speaking. Other works [47][48][49][50] are all to identify the text written by the user through the recording, which cannot be used in high noise. Sound-based Gesture Recognition and Location: SoundWave [51], DopLink [31], AirLink [52], Multiwave [46] and AudioGest [45] are sound-based gesture recognition systems using the doppler effect.…”

Section: Related Workmentioning

confidence: 99%

Towards practical 3D ultrasound sensing on commercial-off-the-shelf mobile devices

Zhai

Tang

et al. 2021

Computer Networks

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“…It can recognize the text inputting from the keyboard outline printed on the conventional surfaces (e.g., wood table). SoundWrite [102] and SoundWrite II [103] recognize the stroke according to the sound signal generated by moving the finger on the surface (e.g., table, paper). They leverage the microphone to capture the acoustic signal, extract frequency and time features, and recognize stroking by pattern classification.…”

Section: A Passive Acoustic Sensingmentioning

confidence: 99%

Hand Gesture Recognition Based on Active Ultrasonic Sensing of Smartphone: A Survey

et al. 2019

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With the rapid development of Internet of Things, hand gesture recognition has drawn wide attention in the field of ubiquitous computing because it provides us with simple and natural human-computer interaction mode. Among these various implementations, hand gesture recognition using ultrasonic signals of smartphone has become a hot research topic due to its various advantages. In this paper, we consider the smartphone as an active sonar sensing system to identify hand movements. Specifically, the speakers emit ultrasonic signal and the microphone on the same phone receives the changed echo affected by hand movements. This paper investigates the state-of-the-art hand gesture applications and presents a comprehensive survey on the characteristics of studies using the active sonar sensing system. Firstly, we review the existing research of hand gesture recognition based on acoustic signals. After that, we introduce the characteristics of ultrasonic signal and describe the fundamental principle of hand gesture recognition. Then, we focus on the typical methods used in these studies and present a detailed analysis on signal generation, feature extraction, preprocessing, and recognition methods. Next, we investigate the state-of-the-art ultrasonic-based applications of hand gesture recognition using smartphone and analyze them in detail from dynamic gesture recognition and hand tracking. Afterwards, we make a discussion about these systems from signal acquisition, signal processing, and performance evaluation to obtain some insight into development of the ultrasonic hand gesture recognition system. Finally, we conclude by discussing the challenges, insight, and open issues involved in hand gesture recognition based on ultrasonic signal of the smartphone.

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SoundWrite II: Ambient Acoustic Sensing for Noise Tolerant Device-Free Gesture Recognition

Cited by 9 publications

References 4 publications

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Towards practical 3D ultrasound sensing on commercial-off-the-shelf mobile devices

Hand Gesture Recognition Based on Active Ultrasonic Sensing of Smartphone: A Survey

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