A kilohertz kilotaxel tactile sensor array for investigating spatiotemporal features in neuromorphic touch

Lee, Wang Wei; Kukreja, Sunil L.; Thakor, Nitish V.

doi:10.1109/biocas.2015.7348412

Cited by 37 publications

(24 citation statements)

References 15 publications

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“…We previously reported a high speed tactile sensing platform to investigate the use of spatiotemporal coding in touch (Lee et al, 2015 ). It has 4096 piezoresistive sensing elements arranged in a 64 × 64 grid.…”

Section: Methodsmentioning

confidence: 99%

Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks

2017

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This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications.

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Section: Methodsmentioning

confidence: 99%

Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks

2017

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“…In addition, the research also needs to deal with challenges related to data acquisition, such as trade-off between the spatial resolution and temporal resolution, simultaneous sensing of multiple stimuli, etc. [ 128 , 129 , 130 , 131 ]. The massive amount of tactile signals need to be acquired at high rates.…”

Section: Intelligent Signal Processing For Smart Tactile Sensingmentioning

confidence: 99%

“…However, the increase of the number of tactile sensors limits the speed to collect the data. To provide fast sampling rate with high spatial resolution, Lee et al took advantage of parallel processing properties of Field Programmable Gate Array (FPGA) and developed a tactile sensing system with high spatiotemporal resolution [ 128 ]. Based on the theory of compressed sensing, Hollis et al proposed a novel strategy to reduce hardware complexity and addressed the scalability challenges of tactile signals acquisition [ 129 ].…”

Section: Intelligent Signal Processing For Smart Tactile Sensingmentioning

confidence: 99%

Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review

Zou

Wang

et al. 2017

Sensors

221

110

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During the last decades, smart tactile sensing systems based on different sensing techniques have been developed due to their high potential in industry and biomedical engineering. However, smart tactile sensing technologies and systems are still in their infancy, as many technological and system issues remain unresolved and require strong interdisciplinary efforts to address them. This paper provides an overview of smart tactile sensing systems, with a focus on signal processing technologies used to interpret the measured information from tactile sensors and/or sensors for other sensory modalities. The tactile sensing transduction and principles, fabrication and structures are also discussed with their merits and demerits. Finally, the challenges that tactile sensing technology needs to overcome are highlighted.

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“…Applications based on integration with sensory modalities of humans have been widely explored. These include applications based on tactile sensor arrays by Lee et al [122] and Ros et al [123]. Corradi et al [124] discuss directions for development of a neuromorphic vestibular system, while an autonomous neuromorphic cognition system has been proposed by Chicca et al [125].…”

Section: Applications In Perception Engineeringmentioning

confidence: 99%

Recent trends in neuromorphic engineering

Soman

Jayadeva

2016

Big Data Anal

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Neuromorphic Engineering has emerged as an exciting research area, primarily owing to the paradigm shift from conventional computing architectures to data-driven, cognitive computing. There is a diversity of work in the literature pertaining to neuromorphic systems, devices and circuits. This review looks at recent trends in neuromorphic engineering and its sub-domains, with an attempt to identify key research directions that would assume significance in the future. We hope that this review would serve as a handy reference to both beginners and experts, and provide a glimpse into the broad spectrum of applications of neuromorphic hardware and algorithms. Our survey indicates that neuromorphic engineering holds a promising future, particularly with growing data volumes, and the imminent need for intelligent, versatile computing.

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A kilohertz kilotaxel tactile sensor array for investigating spatiotemporal features in neuromorphic touch

Cited by 37 publications

References 15 publications

Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks

Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks

Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review

Recent trends in neuromorphic engineering

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