Design biomedical instrumentation systems

Describe the unique challenges of measuring signals from living systems (e.g., safety, artifacts, variability).

Define key characteristics of biomedical signals, including typical amplitude and frequency ranges.

Analyze operational amplifier (op-amp) circuits to determine gain, input impedance, and bandwidth.

Apply active and passive filter concepts to design for specific biomedical frequency bands.

Calculate the Common-Mode Rejection Ratio (CMRR) and its importance in noise cancellation.

Identify common sources of noise in biomedical measurements and calculate the signal-to-noise ratio (SNR).

Explain the ionic basis of resting and action potentials in excitable cells (neurons, muscle cells).

Describe the basic structure and function of the peripheral and central nervous systems.

Model the electrode-electrolyte interface and explain the origin of half-cell potential.

Compare the characteristics and applications of surface, needle, and microelectrodes.

Select an appropriate transducer (e.g., resistive, capacitive, piezoelectric) for a given physiological measurement.

Apply proper skin preparation techniques to minimize electrode contact impedance and motion artifacts.

Describe the heart's electrical conduction system and its relation to the cardiac cycle.

Explain Einthoven's triangle and the configuration of the 12-lead ECG system.

Identify P, QRS, and T waves on an ECG trace and measure key intervals (PR, QRS duration, QT).

Design a complete ECG acquisition system, specifying amplifier, filter, and safety requirements.

Calculate instantaneous and average heart rate from an ECG recording.

Describe the principles of photoplethysmography (PPG) for heart rate monitoring.

Compare direct (invasive) and indirect (non-invasive) methods of blood pressure measurement.

Explain the principles of auscultatory and oscillometric blood pressure devices.

Describe the use of catheter-transducer systems for invasive hemodynamic monitoring.

Explain the principles of electromagnetic and ultrasonic Doppler techniques for blood flow measurement.

Describe indicator dilution and thermodilution methods for measuring cardiac output.

Describe the neurophysiological origin of EEG signals from cortical neuron populations.

Explain the 10-20 international system for electrode placement and different montage types.

Design an EEG acquisition system with appropriate specifications for amplification, filtering, and grounding.

Identify and apply techniques to mitigate common EEG artifacts (e.g., EOG, EMG, 60Hz noise).

Select appropriate ADC sampling rates and resolution for high-fidelity EEG recording.

Differentiate between spontaneous EEG, event-related potentials (ERPs), and steady-state evoked potentials (SSEPs).

Apply spectral analysis (FFT) to identify EEG frequency bands (delta, theta, alpha, beta, gamma).

Correlate specific EEG frequency band activity with cognitive and emotional states (e.g., arousal, attention, relaxation).

Perform quantitative EEG (qEEG) analysis to create topographical brain maps.

Describe the process of averaging to extract event-related potentials (ERPs) from raw EEG data.

Analyze ERP components (e.g., P300, N400) in the context of cognitive tasks.

Differentiate between surface EMG (sEMG) and intramuscular EMG recordings and their applications.

Design an EMG acquisition system and apply signal processing (rectification, integration) to quantify muscle activity.

Explain the physiological basis of Electrodermal Activity (EDA) and its relation to sympathetic nervous system arousal.

Calculate time-domain and frequency-domain Heart Rate Variability (HRV) parameters as markers of autonomic function.

Describe the principles of Electrooculography (EOG) for tracking eye movements and detecting blinks.

Propose a multimodal sensor configuration (e.g., EEG, HRV, EDA) to assess stress or emotional state.

Explain the operating principles of accelerometers and gyroscopes for motion tracking.

Apply sensor fusion techniques to combine data from multiple motion sensors for robust orientation and activity detection.

Design an instrumentation setup to measure motor responses, such as reaction time and movement tracking.

Describe methods for analyzing behavioral patterns from continuous wearable sensor data.

Explain the role of context-aware computing in interpreting physiological and behavioral data.

Explain the basic principles of X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI).

Describe the principle of diagnostic ultrasound for imaging soft tissues.

Explain the principles of spirometry for measuring lung volumes and capacities.

Describe the working principle of a pulse oximeter for measuring blood oxygen saturation (SpO2).

Describe the principles of biochemical sensors for measuring pH, pO2, pCO2, and glucose.

Describe the architecture of a biotelemetry system for wireless physiological monitoring.

Analyze design trade-offs in wearable sensors, including power consumption, form factor, and data transmission.

Explain the concept of a biofeedback loop and its application in therapeutic interventions.

Describe how neurofeedback systems use real-time EEG analysis for brain training.

Discuss the role of machine learning in artifact removal, feature extraction, and classification of physiological states.

Evaluate the design of a microprocessor-based system for a specific medical instrumentation application.