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IDNE 701 · Introduction to Neuroengineering · FA26 Edition

Multimodal Neuroimaging &
Diagnostic Biomarker Systems

A 14-week semester trajectory from clinical neuropathology to physical sensor design, reconstruction algorithms, safety validation, and regulatory translation.

Discovery & Clinical Framing (1-3)
Biophysics & Sensors (4-6)
Architecture & Midterm (7-9)
Safety & Regulation (10-12)
Verification & Pitch (13-14)
Week 1 · Aug 28 Course Launch, Team Formation & Diagnostic Challenges
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Student Tasks
  • Form interdisciplinary teams (3–4 students blending engineering, computing, and neurobiology skills).
  • Select a target neurological or psychiatric disorder (e.g., Early Alzheimer's, Traumatic Brain Injury, Drug-Resistant Epilepsy, Parkinsonian Subtypes, Stroke Recovery).
  • Review the foundational Neuroengineering Knowledge Base and terminology in the Glossary.
  • Establish team collaboration protocols, GitHub repository, and shared documentation workspace.
Instructor Actions
Events & Deadlines
  • Course Kickoff: Scope, project charter, and team formation salon.
  • Due: Team Formation & Collaboration Charter.
Time Division
40%
35%
25%
Team formation & charter Disease literature review Project scoping
Week 2 · Sep 04 Neuropathology, Clinical Stakeholders & Biomarker Definition
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Student Tasks
Instructor Actions
Time Division
45%
35%
20%
Pathology & biomarker mapping Stakeholder needs interview Target specifications
Week 3 · Sep 11 Precedents & Lab Visit: UAB Research MRI Core Lab Tour I
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Student Tasks
Instructor Actions
  • Lead guided lab tour of the UAB Research MRI Core facilities.
  • Demonstrate live pulse sequence execution, phantom scanning, and RF head coil hardware.
  • Review and provide formative feedback on Phase 1 team project charters.
Events & Deadlines
Time Division
40%
30%
30%
MRI Core on-site tour Precedent benchmarking Phase 1 dossier synthesis
Week 4 · Sep 18 Biophysical Contrast Mechanisms & Signal Transduction
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Student Tasks
  • Worksheet 4.1: Biophysical Forward Modeling & Signal Transduction — Formulate governing differential equations, compute depth attenuation, and establish theoretical SNR boundaries.
  • Model the fundamental biophysics of your team's primary sensing modality:
    • Nuclear spin dynamics, \(T_1 / T_2 / T_2^*\) relaxation, and BOLD contrast in fMRI.
    • Photons in scattering tissue, Beer-Lambert law, and oxy/deoxy-hemoglobin absorption in fNIRS.
    • Dipole sources, volume conduction, and Poisson equation in EEG and MEG.
    • Acoustic wave propagation and microbubble dynamics in focused ultrasound.
  • Calculate theoretical Signal-to-Noise Ratio (SNR) and spatiotemporal resolution boundaries for your target tissue depth.
Instructor Actions
Events
Time Division
50%
30%
20%
Biophysical modeling SNR & resolution bounds Literature calibration
Week 5 · Sep 25 Optical Imaging & In-Class fNIRS Demonstration Live Demo
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Student Tasks
  • Alumni Speaker Session: Attend opening talk and Q&A with Adeel Memon, MD, PhD (program alumnus and its first graduate) at the start of class.
  • Worksheet 5.1: In-Class fNIRS Demonstration & Hemodynamic Inversion Lab — Invert dual-wavelength optical density to micromolar \([\text{HbO}]\) and \([\text{HbR}]\), evaluate DPF scaling, and simulate bedside biomarkers.
  • Participate in live in-class fNIRS system demonstration (continuous-wave & frequency-domain optical topography).
  • Collect and inspect real-time optical brain hemodynamic signals (\(\Delta[\text{HbO}]\), \(\Delta[\text{HbR}]\), regional cerebral oxygen saturation \(\text{rSO}_2\)).
  • Grand Challenge 06 Application: Analyze fractional tissue oxygen extraction (\(\text{FTOE} = \frac{\text{SpO}_2 - \text{rSO}_2}{\text{SpO}_2}\)) as a bedside biomarker for neonatal hypoxic-ischemic encephalopathy (HIE) and autoregulation failure.
  • Compare optical absorption spectra and light diffusion through thin neonatal calvarium vs adult layered media.
Instructor Actions
  • Introduce alumni guest speaker Adeel Memon, MD, PhD (first graduate of the program) for opening talk to the class.
  • Deliver lecture: Optical Neuroimaging: Diffuse Optics, fNIRS & Bedside Hemodynamics (Slides).
  • Conduct live in-class fNIRS demonstration using multi-channel research cap system.
  • Demonstrate real-time modified Beer-Lambert transformation, motion artifact removal (spline / wavelet filtering for uncooperative neonatal subjects), and optode coupling.
Events
  • Alumni Guest Speaker: Adeel Memon, MD, PhD (alumnus of the program and its first graduate) speaking to the class at the start of class.
  • Live In-Class Demonstration: Multi-channel fNIRS hemodynamic recording, ambient light rejection, and neonatal \(\text{rSO}_2\)/\(\text{FTOE}\) physiological modeling with Worksheet 5.1.
Time Division
45%
35%
20%
fNIRS demo & data parsing Beer-Lambert inversion & DPF Bedside biomarker analysis
Week 6 · Oct 02 Sensor Hardware, Transduction Physics & Array Architecture
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Student Tasks
  • Worksheet 6.1: Sensor Array Architecture & Front-End Noise Budget — Design multi-channel transducer geometry, calculate Johnson-Nyquist thermal limits, and model spatial sensitivity fields.
  • Design the physical transducer / sensor geometry (e.g., phased-array RF coils, optode source-detector geometry, active EEG electrode layouts, capacitive sensors).
  • Analyze impedance matching, geometric decoupling, optical fiber coupling, or analog front-end (AFE) amplification stages.
  • Simulate the spatial sensitivity profile (e.g., \(B_1^-\) receive sensitivity, photon banana distribution in brain tissue, lead field matrices).
  • Review comparative trade-offs between invasive vs non-invasive sensing modalities (ECoG vs EEG vs fNIRS).
  • Prepare preliminary presentation slides and system diagrams for next week's Mid-Semester Design Review.
Instructor Actions
Events
  • Hardware Design Studio: Array geometry and front-end noise budget optimization with Worksheet 6.1.
Time Division
40%
35%
25%
Sensor array design Sensitivity field modeling Midterm PDR dossier prep
Week 7 · Oct 09 Mid-Semester Milestone: Concept Pin-Up & Preliminary Design Review ★ Milestone
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Student Tasks
  • Present 12-minute team pitch with visual concept boards and preliminary technical block diagrams.
  • Defend selection of biophysical contrast mechanism, sensor geometry, and expected biomarker resolution.
  • Submit Mid-Semester Deliverable: Preliminary Design Concept (PDC) & Biomarker Architecture Dossier.
  • Participate in peer critique and complete structured rubrics using Worksheet 7.1: Preliminary Design Review (PDR) Rubric for two other team presentations.
Instructor Actions
  • Coordinate faculty review panel and industry mentors for presentation critique using the Worksheet 7.1 Evaluation Matrix.
  • Moderate design review salon and facilitate cross-team engineering critique.
  • Provide compiled rubric evaluations and written milestone feedback within 5 days.
Events & Deadlines
  • Mid-Semester Review Colloquium: Team presentations, concept pin-up gallery, and feedback reception.
  • Due: Mid-Semester Deliverable — Preliminary Design Concept (PDC) & Biomarker Architecture Dossier.
Time Division
50%
30%
20%
Design presentation & defense Panel Q&A & critique Peer review assessment
Week 8 · Oct 16 Signal Acquisition, Sampling Schemes & Pulse Sequences
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Student Tasks
  • Design the spatial encoding and temporal sampling scheme (e.g., 2D/3D k-space trajectories, EPI, spiral readouts, EEG temporal montage sampling, multiplexed optical source modulation).
  • Evaluate the Nyquist-Shannon sampling limits, spatial aliasing, and gradient timing constraints.
  • Calculate scan time / acquisition latency vs point spread function (PSF) blurring trade-offs.
  • Draft the mathematical signal model: \(S(t) = \int \rho(\mathbf{r}) e^{-i \mathbf{k}(t) \cdot \mathbf{r}} d\mathbf{r}\).
Instructor Actions
Events
  • Workshop: Pulse sequence timing diagrams and k-space trajectory design.
Time Division
45%
35%
20%
Acquisition & sequence design K-space / sampling simulation Timing budget analysis
Week 9 · Oct 23 Lab Visit: Clinical EMU & Neuroengineering EEG Core Lab Tour II
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Student Tasks
  • Visit the Clinical Epilepsy Monitoring Unit (EMU) & Neuroengineering EEG Core (Lab Guide & Protocol) for hands-on high-density EEG (128/256 channel) setup and impedance measurement.
  • Observe continuous long-term video-EEG and neonatal amplitude-integrated EEG (aEEG) monitoring for bedside seizure detection.
  • Inspect Faradaic cage electromagnetic shielding, active coaxial cable driving, and Driven Right Leg (DRL) common-mode noise cancellation.
  • Analyze neonatal burst-suppression patterns and electrographic seizures during therapeutic hypothermia for HIE.
  • Compare electrophysiological temporal resolution (\(< 1\,\text{ms}\)) against metabolic and hemodynamic imaging modalities.
Instructor Actions
  • Host guided clinical and laboratory tour of the Clinical EMU and Neuroengineering EEG Core facilities using the Lab Tour Guide.
  • Demonstrate electrode impedance checking (\(Z < 5\,\text{k}\Omega\)), active shielding, noise cancellation, and ERP data acquisition.
  • Review clinical seizure onset marking, electrode pop artifacts, and continuous bedside aEEG trends.
Events
  • Lab Tour II: Clinical Epilepsy Monitoring Unit (EMU) & Neuroengineering EEG Core (Electrophysiology Suites, Faradaic Shielded Rooms).
Time Division
40%
35%
25%
EMU & EEG Core lab tour Montage setup & impedance test aEEG seizure data review
Week 10 · Oct 30 Artifact Mitigation, Motion Correction & SNR Optimization
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Student Tasks
  • Identify system-specific noise sources (e.g., patient motion, cardiac/respiratory pulsatility, eddy currents, \(B_0\) field inhomogeneities, eye blinks).
  • Incorporate real-time or prospective motion correction (navigators, optical tracking, ICA filtering, retrospective phase correction).
  • Demonstrate robustness of biomarker detection in the presence of synthetic noise and patient movement.
  • Formulate the signal processing flow chart and computational latency budget.
Instructor Actions
Events
  • Clinic Simulation: Stress-testing student algorithms against corrupt and noisy clinical datasets.
Time Division
40%
35%
25%
Artifact filtering & motion correction Algorithm stress testing Latency optimization
Week 11 · Nov 06 Reconstruction Pipelines & Machine Learning Biomarker Extraction
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Student Tasks
  • Implement reconstruction algorithms (Inverse Fast Fourier Transform [IFFT], SENSE/GRAPPA parallel imaging, or minimum norm estimate [MNE] source localization).
  • Build computational pipeline for feature extraction, dimensionality reduction, or deep neural network biomarker classification (see Machine Learning in BCI and Kalman Filtering).
  • Quantify reconstruction error (RMSE, SSIM) and biomarker classification accuracy (ROC-AUC, Confusion Matrix).
  • Implement baseline synthetic data test bench to benchmark reconstruction fidelity on neonatal aEEG / fNIRS time series.
Instructor Actions
  • Deliver lecture: Inverse Problems, Compressed Sensing, and Deep Learning in Neuroimage Reconstruction (Slides).
  • Provide open neuroimaging benchmark datasets (OASIS, ADNI, HCP, PhysioNet) and neonatal NICU aEEG/fNIRS time series.
  • Code walkthrough: PyTorch / TensorFlow pipelines for accelerated image reconstruction and biomarker inference.
  • Distribute FDA regulatory guidance documents (510(k) vs PMA, Early Feasibility, Q-Submission protocol) in preparation for Week 12.
Events
  • Hackathon Session: Algorithm sprint for reconstruction acceleration and biomarker detection.
Time Division
50%
30%
20%
Reconstruction algorithm coding ML biomarker training Regulatory framework drafting
Week 12 · Nov 13 Safety Limits (SAR, Thermal, Optical) & FDA Regulatory Strategy
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Student Tasks
  • Perform quantitative safety and dose modeling for your device:
    • Specific Absorption Rate (SAR in W/kg), \(B_1^+\) RMS, and peripheral nerve stimulation (PNS) thresholds in MRI.
    • Maximum Permissible Exposure (MPE) and tissue heating limits (ANSI Z136.1) in optical / fNIRS systems.
    • Thermal index (TI), mechanical index (MI), and spatial-peak temporal-average intensity (\(I_{\text{spta}}\)) in ultrasound.
    • Electrical leakage current and patient isolation (IEC 60601-1) in EEG.
  • Formulate FDA classification strategy (Class II 510(k) predicate vs De Novo vs Class III PMA) and draft an Early Feasibility / IDE plan.
  • Address ethical considerations in diagnostic neuroimaging (see Neuroethics & Translation).
Instructor Actions
Events
  • Regulatory Clinic: Risk analysis, predicate device search, and FDA Pre-Submission strategy.
Time Division
45%
30%
25%
SAR & safety physics FDA regulatory roadmap Risk matrix & FMEA
Week 13 · Nov 20 Verification, Virtual Prototyping & Clinical Protocol (IRB)
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Student Tasks
  • Synthesize complete end-to-end virtual simulation demo showing:
    • Simulated diseased vs healthy neural substrate.
    • Sensor array signal acquisition with noise models.
    • Reconstruction and ML diagnostic output dashboard.
  • Draft a full Human Subjects Clinical Validation Protocol (IRB proposal with inclusion/exclusion criteria, primary endpoints, statistical power).
  • Compile the final Technical Design Dossier chapters and prepare pitch slides.
Instructor Actions
Events
  • Dry Run & Pitch Coaching: Rapid-fire feedback on pitch structure and technical demonstration.
Time Division
50%
30%
20%
Virtual prototype simulation IRB clinical protocol draft Dossier compilation
🦃 Nov 27: Thanksgiving Break · No Scheduled Class Sessions · Final Polish Week
Week 14 · Dec 04–11 Final Milestone: Grand Pitch Symposium & Deliverable Showcase ★ Final Milestone
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Student Tasks
  • Deliver 15-minute public pitch + live interactive simulation demonstration according to the Grand Pitch Symposium Guidelines to guest faculty, clinicians, and industry evaluators.
  • Defend the end-to-end design: Clinical impact, biophysical validation, hardware architecture, reconstruction algorithm, safety, and regulatory pathway.
  • Submit the final course deliverable package:
    • Deliverable 1: Complete Technical Design Dossier & Regulatory Strategy (PDF).
    • Deliverable 2: Reproducible Simulation & Reconstruction Codebase (GitHub repo with documentation).
    • Deliverable 3: Executive Pitch Deck & One-Page Clinical Brief.
  • Complete peer team evaluations and course retrospectives.
Instructor Actions
  • Host and moderate the IDNE 701 Grand Pitch Symposium with invited panel judges.
  • Tabulate final evaluations and award Best Innovation, Neonatal Translation Excellence, and Best Engineering Design awards.
  • Publish selected project showcases to the program website and archive materials.
Events & Deadlines
  • Grand Pitch Symposium: Final formal presentations, live software demos, and award ceremony.
  • Due: Final Course Deliverable Package (Dossier PDF, Simulation Codebase repo, Executive Pitch Deck).
Time Division
60%
40%
Final symposium pitch & demo Dossier submission & debrief

Biophysical Contrast & Transduction

Grounding diagnostic measurements in biological reality — from nuclear spin relaxation and photon scattering to ionic dipole potentials.

Spatiotemporal Resolution Bounds

Navigating the fundamental physical trade-offs across penetration depth, temporal sampling frequency, and voxel/sensor volume.

K-Space & Inverse Problems

Mathematical foundations of spatial encoding, non-Cartesian sampling trajectories, and regularized / compressed sensing reconstruction.

Machine Learning & Biomarker Specificity

Validating feature extraction algorithms against class imbalance, motion confounders, and rigorous out-of-distribution generalization.

SAR, Thermal & Laser Safety

Ensuring patient safety through strict adherence to RF specific absorption rates, optical maximum permissible exposure, and IEC standards.

Regulatory & Clinical Translation

Navigating FDA 510(k)/PMA classification, Early Feasibility IDE protocols, and clinical workflow integration in medical centers.