Spring 2027

Computers in Medicine

Computers in Medicine covers microprocessor-based medical instrumentation, emphasizing real-time ECG analysis through labs and projects involving biomedical digital signal processing algorithms.

offering recorded3 credits
Recorded instructors · Spring 2027 Amit Nimunkar4.0/5

Summary

1 / 3

Recent recorded grades — Spring 2024: 3.48 GPA, 62.5% A/AB (n=24 letter grades); Spring 2025: 3.28 GPA, 62.1% A/AB (n=29 letter grades); Spring 2026: 3.67 GPA, 87.2% A/AB (n=39 letter grades).

What you’ll be able to do

  • Solve complicated mathematical problems with design of digital filters for biomedical signals

  • Build electrocardiogram (ECG) instrumentation system to view their ECG and use it as an input to a microcontroller for signal analysis

  • Employ simulation tools to design and test a variety of linear digital filters

  • Perform experiments, analyze and interpret the performance of digital filters on a database of ECGs

  • Write microcontroller code for real-time processing of biomedical signals, particularly the ECG, to attenuate diverse noise sources and find clinically-significant features

  • Demonstrate an ability to formulate and, independently design and implement digital filters and algorithm to process biomedical signals

Source: UW Guide 1 UW Guide 2

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

E C E 330 and (COMP SCI 200, 220, 300, 301, or placement into COMP SCI 300), graduate/professional standing, or member of Engineering Guest Students

      • ECE 330
      • COMP SCI 200, 220, 300, 301, or placement into COMP SCI 300
      take all
    • graduate/professional standing
    • member of Engineering Guest Students
    take one
BME/ECE 463

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Any of
    • All of
      • ECE 330
      • COMP SCI 200, 220, 300, 301, or placement into COMP SCI 300
    • graduate/professional standing
    • member of Engineering Guest Students

Professors

Spring 2027

Amit Nimunkar

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.25/5 from 28 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

Recent recorded grades — Spring 2024: 3.48 GPA, 62.5% A/AB (n=24 letter grades); Spring 2025: 3.28 GPA, 62.1% A/AB (n=29 letter grades); Spring 2026: 3.67 GPA, 87.2% A/AB (n=39 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

AMIT NIMUNKAR is recorded teaching in Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 320
LAB 301Classroom Instruction0 / 160
LAB 302Classroom Instruction0 / 160
LEC 001Classroom Instruction0 / 200
LAB 301Classroom Instruction0 / 100
LAB 302Classroom Instruction0 / 100

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
Download part 1

Student experience

the class

Recent recorded grades — Spring 2024: 3.48 GPA, 62.5% A/AB (n=24 letter grades); Spring 2025: 3.28 GPA, 62.1% A/AB (n=29 letter grades); Spring 2026: 3.67 GPA, 87.2% A/AB (n=39 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Microprocessor-based medical instrumentation
  • Real-time analysis of electrocardiograms
  • Design and testing of linear digital filters
  • Noise attenuation and feature extraction in biomedical signals

Skills

  • Design and implement digital filters and algorithms for biomedical signal processing
  • Build ECG instrumentation systems connected to microcontrollers
  • Use simulation tools to design and test linear digital filters
  • Write microcontroller code for real-time biomedical signal processing

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records
BME/ECE 463 · Spring 2027

Computers in Medicine

Recorded 2026-10-14
BME/ECE 463 · Spring 2027

Computers in Medicine

Recorded 2026-10-14
Raw records 
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Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
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  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "838fb940f15705049ef0cd72eb5cabfedb79a8d60463736e123a212162069633",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
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}