BIOMEDICAL SENSORS | Università degli studi di Bergamo - Didattica e Rubrica

BIOMEDICAL SENSORS

Modulo Generico
Codice dell'attività formativa: 
148008-M2

Scheda dell'insegnamento

Per studenti immatricolati al 1° anno a.a.: 
2021/2022
Insegnamento (nome in italiano): 
BIOMEDICAL SENSORS
Insegnamento (nome in inglese): 
Biomedical sensors
Tipo di attività formativa: 
Attività formativa Affine/Integrativa
Tipo di insegnamento: 
Opzionale
Settore disciplinare: 
ELETTRONICA (ING-INF/01)
Anno di corso: 
2
Anno accademico di offerta: 
2022/2023
Crediti: 
6
Responsabile della didattica: 
Altri docenti: 
Mutuazioni
  • Corso di studi in ENGINEERING AND MANAGEMENT FOR HEALTH - Percorso formativo in COMUNE
  • Corso di studi in MECCATRONICA E SMART TECHNOLOGY ENGINEERING - Percorso formativo in SMART TECHNOLOGY ENGINEERING

Altre informazioni sull'insegnamento

Modalità di erogazione: 
Didattica Convenzionale
Lingua: 
Inglese
Ciclo: 
Primo Semestre
Obbligo di frequenza: 
No
Ore di attività frontale: 
48
Ore di studio individuale: 
90
Ambito: 
Attività formative affini o integrative
Prerequisites

Basic electronics.

Educational goals

The course gives an overview of devices and techniques that are used in sensors and electronic systems for Internet-of-Things. The course targets applications impacting on people (monitoring of physiological parameters), on their interaction with their environment (home, workplace) as well as on advanced industrial technologies (automotive, smart machinery and production equipment).

Course content

1. Introduction
Fundamentals of sensors and mixed-signal microelectronics for IoT systems.

2.Sensors
Passive and active infrared (IR) sensors, microphones, cameras,
GPS, accelerometers, ultrasonic sensors,.

3.Electronics and signal processing
Amplification of sensor signals. Noise. Interferences. Noise from power supplies. PSRR. Signal-to-noise ratio. Power spectral density. Noise sources in electronic circuits. Effects of noise in circuits for the analog processing of signals from sensors.
Signal filtering. Low-pass, high-pass, bandpass filters. Butterworth, Chebyshev, Bessel filters. Filters with operational amplifiers.
Sampling of analog signals. Fourier analysis of sampled signals. Sampling theorem. Aliasing. Antialiasing filters.
Analog-to-digital conversion. Quantization noise. Effective number of bits. A/D converters.
Digital signal processing. Digital filters. DFT and FFT. Spectral leakage and windowing.

4. IoT systems, wireless devices
Microcontrollers and FPGA: architecture and embedded firmware
Wireless communication techniques, protocols and networks for IoT systems (Bluetooth, LoRaWAN)

Teaching methods

Classroom lectures, experimental activities in the electronics lab

Assessment and Evaluation

Oral exam at the end of the course.