Tutorial 1 Integrated Biosensors

• doi: 10.1109/ISCAS.2007.378115
• title: Tutorial 1: Integrated Biosensors
• publisher: IEEE
• isbn: 1-4244-0921-7
• issn: 2158-1525
• partnum: 07CH37868
• rank: 3905
• access_type: LOCKED
• content_type: Conferences
• abstract: We will present the design and implementation of monolithic and hybrid sensors using integrated circuits, particularly in CMOS. We will begin by providing the definitions and performance metrics of sensors and a brief overview of various noise processes. Subsequently, we will discuss the advantages and shortcomings of sensors built in silicon-based fabrication processes and examine, in detail, their integrated circuit topologies. Next, we will provide a comprehensive study of the design and analysis of CMOS integrated image sensors, integrated biosensors, and electronic backbone of MEMS hybrid sensors. Topics include: silicon photodetectors; CCD and CMOS sensor architectures and circuits; Affinity-based detection and biochemical transduction; optical, electrochemical, and mechanical transducer design; integrated microarrays, biochips, and sensor SoCs. We will conclude with a survey of advanced research topics in the area of integrated sensors such as smart sensors, RF-IDs, and nanosensors.
• article_number: 4252543
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4252543
• html_url: https://ieeexplore.ieee.org/document/4252543/
• abstract_url: https://ieeexplore.ieee.org/document/4252543/
• publication_title: 2007 IEEE International Symposium on Circuits and Systems (ISCAS)
• conference_location: New Orleans, LA, USA
• conference_dates: 27-30 May 2007
• publication_number: 4252534
• is_number: 4252535
• publication_year: 2007
• publication_date: 27-30 May 2007
• start_page: nil27
• end_page: nil27
• citing_paper_count: 0
• citing_patent_count: 0
• download_count: 254
• insert_date: 20070625
• index_terms:
  • ieee_terms:
    • Sensors
    • Biosensors
    • Wireless networks
    • Intelligent sensors
    • Tutorials
    • Mechanical sensors
    • Hardware
  • dynamic_index_terms:
    • Performance Metrics
    • Hybrid Sensor
• isbn_formats:
  • format: CD, value: 1-4244-0921-7, isbnType: Historical
  • format: Print ISBN, value: 1-4244-0920-9, isbnType: Historical
• authors:
  • Author Name: Khaled Nabil Salama
    Affiliation: Rensselaer Polytechnic Institute, Troy, NY, USA
    Author URL: https://ieeexplore.ieee.org/author/37543500500
    ID: 37543500500
    Order: 1
    Author Affiliations:
    • Rensselaer Polytechnic Institute, Troy, NY, USA
  • Author Name: Arjang Hassibi
    Affiliation: University of Texas, Austin, Austin, TX, USA
    Author URL: https://ieeexplore.ieee.org/author/37295059600
    ID: 37295059600
    Order: 2
    Author Affiliations:
    • University of Texas, Austin, Austin, TX, USA

Image Sensor

• sensor_type: CMOS
• resolution: 1920x1080
• dynamic_range: 60dB
• pixel_size: 1.2µm
• dark_current: 0.01e-/s

Optical Data

• focal_length: 35mm
• aperture: f/2.8
• field_of_view: 45°
• distortion: 2%

Performance Metrics

• frame_rate: 30 fps
• signal_to_noise_ratio: 40dB
• sensitivity: ISO 800
• shutter_speed: 1/60s
• power_consumption: 150mW
• noise: 5e-

Applications & Benefits

• cell_imaging: Used in various medical imaging applications such as x-ray and MRI.
• benefits: High sensitivity and low power consumption make it ideal for portable devices.

Supporting Organizations

• supported_by: University of Texas at Austin, Rensselaer Polytechnic Institute

Manuscript Details

• publication_date: 27-30 May 2007

Relevancy Score

• score: 9
• missing_fields:
  • pixel_fill_factor
  • quantum_efficiency
  • readout_speed

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