TY - JOUR
T1 - Large-area electronics
T2 - A platform for next-generation human-computer interfaces
AU - Sanz-Robinson, Josue
AU - Moy, Tiffany
AU - Huang, Liechao
AU - Rieutort-Louis, Warren
AU - Hu, Yingzhe
AU - Wagner, Sigurd
AU - Sturm, James C.
AU - Verma, Naveen
N1 - Publisher Copyright:
© 2011 IEEE.
PY - 2017/3
Y1 - 2017/3
N2 - Large-area electronics (LAE) is a compelling platform for developing the next generation of human-computer interfaces (HCIs). These systems aim to provide natural interfaces that do not rely on the user providing active and explicit inputs. Instead, user intentions should be inferred implicitly from our natural interactions with the environment and with each other, in order to derive inputs. This requires a large number of sensors to detect signals from interactions and signal-processing to infer the intentions. LAE is a well-suited technology for creating the sensors, enabling these to be diverse and distributed but also conformal. This eases integration in/on environmental and personal surfaces. In order to address the signal-processing required, as well as the other system functions, we develop hybrid LAE/CMOS architectures, which exploit the complementary strengths of the two technologies. We demonstrate the hybrid architectures in several testbed systems, and focus on two of these as case studies: 1) A source separation system, which uses a large-area microphone array to separate the voice of multiple simultaneous speakers in a room; 2) An electroencephalogram (EEG) acquisition and biomarker-extraction system based on flexible, thin-film electronics.
AB - Large-area electronics (LAE) is a compelling platform for developing the next generation of human-computer interfaces (HCIs). These systems aim to provide natural interfaces that do not rely on the user providing active and explicit inputs. Instead, user intentions should be inferred implicitly from our natural interactions with the environment and with each other, in order to derive inputs. This requires a large number of sensors to detect signals from interactions and signal-processing to infer the intentions. LAE is a well-suited technology for creating the sensors, enabling these to be diverse and distributed but also conformal. This eases integration in/on environmental and personal surfaces. In order to address the signal-processing required, as well as the other system functions, we develop hybrid LAE/CMOS architectures, which exploit the complementary strengths of the two technologies. We demonstrate the hybrid architectures in several testbed systems, and focus on two of these as case studies: 1) A source separation system, which uses a large-area microphone array to separate the voice of multiple simultaneous speakers in a room; 2) An electroencephalogram (EEG) acquisition and biomarker-extraction system based on flexible, thin-film electronics.
KW - TFT
KW - a-Si
KW - electroencephalogram (EEG)
KW - human-computer interfaces (HCIs)
KW - hybrid system
KW - large-area electronics (LAEs)
KW - source separation
UR - http://www.scopus.com/inward/record.url?scp=84997765931&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84997765931&partnerID=8YFLogxK
U2 - 10.1109/JETCAS.2016.2620474
DO - 10.1109/JETCAS.2016.2620474
M3 - Article
AN - SCOPUS:84997765931
SN - 2156-3357
VL - 7
SP - 38
EP - 49
JO - IEEE Journal on Emerging and Selected Topics in Circuits and Systems
JF - IEEE Journal on Emerging and Selected Topics in Circuits and Systems
IS - 1
M1 - 7752794
ER -