Physiology sensor lab
Open your materials, follow the steps, then turn in your work.
Collect physiological data using sensors under controlled conditions.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
2. Start the work
Set up the sensor and calibrate it per the protocol.
Show all 5 required steps
- Set up the sensor and calibrate it per the protocol.
- Record baseline and treatment measurements for each trial.
- Repeat trials to capture variation.
- Log all readings in a structured data table.
- Submit your raw data table.
Lost your place? Lost your place? You should have the sensor calibrated per protocol (step 1) and baseline plus treatment readings started (step 2). Pick up by repeating trials to capture variation (step 3), logging every reading in your structured table (step 4), then submit the raw table.
Check your work before submitting
- Your data table records repeated, labeled trials.
- You can describe how you controlled conditions.
Before lab work: read the safety rules
- Wash hands before placing any sensor on a participant.
- Do not share sensor components that contact skin without wiping with an alcohol swab between uses.
- Stop the trial immediately if a participant reports discomfort, dizziness, or pain.
- Do not collect data on a participant who has not verbally consented for this class activity.
- Follow the instructor's calibration protocol exactly -- do not skip steps.
- Store sensor equipment in the labeled case when not in use; report any damage immediately.
3. Turn in your work
DueCheck Schoology- Hand in
- Raw physiology data table: labeled trials, baseline and treatment conditions, measurement values with units, and a brief condition-control note.
How to submit and name your file
Use the submission route shown on today's today's page.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
PDF upload helpYou get two school days for every day you were absent, so this deadline moves with you.
How this lesson connects
Keep using what you learned last class: Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy. Today: Single readings hide normal variation, so repeated, calibrated, real-time trials are required for a data table to count as reproducible scientific evidence.
Optional: listen or watch a unit review▸
Need help? Warm-up, timing, and directions▸
💡 Big idea: Single readings hide normal variation, so repeated, calibrated, real-time trials are required for a to count as reproducible scientific evidence.
- 0-10 and calibration check: set up sensor, verify calibration, and confirm is open
- 10-20Baseline trials: record baseline measurements for each participant or condition
- 20-50Treatment trials: apply the and record all readings per trial
- 50-65Repeat trials as needed to capture natural variation; log all readings
- 65-75Submit raw before leaving the lab area
- 75-80Exit note: describe how you controlled conditions and whether anything went wrong
- • Today is the hands-on data collection session for Problem 2.
- • Bring your pre-lab and your hypothesis -- you should already know what you expect to see before you touch the sensor.
- • Every trial you run goes directly into the table in real time. No copying from memory after the fact.
- • Lab SOPs and Microbiology Testing on WebXam 072125 both test your ability to follow protocols and record data correctly.
- • How to calibrate and operate a physiological sensor following a written protocol (Lab SOP).
- • Why repeating trials and recording each reading separately is essential for reliable conclusions.
- • How a structured with labeled conditions and units enables statistical analysis.
PLTW connection and today's work
Open Problem 2 in your myPLTW course shell and locate the physiology data-collection protocol to review the sensor setup steps and data-table format.
Today's stopping point: The study design and sample-size plan are done; today you run the sensor lab and submit your completed raw data table.
PLTW activity titles identify the course connection. If your account will not open, use the posted materials for today and tell Mr. Mendoza. Do not mark an online activity complete unless you completed it.
Course connection
- Activity 2.1.2 Science and the Media
Use the turn-in directions at the top of this page. Do not create a second submission unless your teacher asks for one.
Show another explanation or a smaller first step
Need help? Choose a starting point
Finish the assigned lab safely before starting extra practice.
Lesson resources: reading, slides, and vocabulary▸
The deck carries the prior idea forward, lets you inspect an analogy, maps the rule to biology, and ends with the same evidence decision and exit ticket used on this page.
Generated from this lesson's canonical data with a red-team citation check.
Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
Single readings hide normal variation, so repeated, calibrated, real-time trials are required for a to count as reproducible scientific evidence.
A research team lays out its question, variables, controls, sampling plan, measurement record, and analysis before deciding what the data support.
- Which variable is changed or compared?
- Which conditions and measurements must stay consistent?
- Which conclusion is inside the study's evidence boundary?
Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
A well-organized classroom study can still be limited by , measurement quality, confounding, and the population represented.
- • Question and variable cards map to the study design.
- • Control and measurement cards map to fair, reproducible data collection.
- • The conclusion card maps to a bounded claim supported by the analysis.
Driving question: Can you run your physiology sensor so cleanly that another group, handed only your protocol and , would get the same readings?
What you already know: Human physiological data can expose and harm a real person, so consent, data minimization, and storage limits exist to protect that person rather than to satisfy bureaucracy.
New idea: Single readings hide normal variation, so repeated, calibrated, real-time trials are required for a to count as reproducible scientific evidence.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Physiology sensor lab. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled system, test, or design relationship and identify which evidence should trigger revision.
- Observe or measure the relevant feature in physiology sensor lab.
- Organize the observation with a stable evidence ID.
- Apply this rule: Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Can you run your physiology sensor so cleanly that another group, handed only your protocol and , would get the same readings?
What the evidence supports: E1-E3 and F1 support the daily take-home when the response meets the stated success criteria.
What it cannot prove: The package does not support claims beyond this lesson's or any real patient diagnosis.
- • : The body's ongoing process of keeping internal conditions like temperature, blood sugar, and pH steady despite changes in the outside environment.
- • physiology: The study of how the body's parts function and work together to keep an organism alive and healthy.
- • biometrics: Measurements of unique body features, such as fingerprints, faces, or eye patterns, used to identify a specific person.
- • mean: The average of a set of numbers, found by adding all the values together and dividing by how many values there are.
- • : A number that measures how spread out data values are around the mean; a small value means values cluster tightly, a large value means they scatter.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
A planned study connects its question to defined variables, controls, sampling, measurement, and analysis so the resulting data can support a bounded and reproducible conclusion.
Limit: A statistical difference or trend does not automatically establish practical importance, causation, generalizability, or freedom from bias.
Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
Limit: A well-organized classroom study can still be limited by , measurement quality, confounding, and the population represented.
Your records repeated, labeled trials.
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
PLTW-BFH-2027-03-04 · Simulated classroom evidence scenario
Your role: biomedical design team member
Decision: Your team must decide what the evidence from physiology sensor lab supports before submitting the labeled and result claim named on today's page.
- • Run repeated trials under the same controls and record each measurement separately in a labeled .
- • Take one careful reading per condition, since you were focused and the sensor was working accurately that trial.
- • Stop and rerun the trials because your table has no way to show normal variation between one reading and another.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the labeled and result claim.
Claim ceiling: Today's evidence supports a classroom claim about physiology sensor lab. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Reason for review: Your team must decide what the evidence from physiology sensor lab supports before submitting the labeled and result claim named on today's page.
Context: Evidence comes from repeated, controlled, real-time measurement, so a that no one could reproduce is not scientific evidence no matter how neat it looks.
- • T1: Set up the sensor and calibrate it per the protocol.
- • T2: Record baseline and treatment measurements for each trial.
- • T3: Repeat trials to capture variation.
- • T4: Log all readings in a structured .
- • T5: Submit your raw .
- • E1: A planned study connects its question to defined variables, controls, sampling, measurement, and analysis so the resulting data can support a bounded and reproducible conclusion.
- • E2: Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
- • E3: Your records repeated, labeled trials.
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Figure finding: Teaching diagram for Physiology sensor lab. Trace the labeled system, test, or design relationship and identify which evidence should trigger revision. This is a teaching model, not patient or experimental data.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Mean = sum of values / number of values. Median = middle ordered value. Range = maximum - minimum.
For 2, 4, 4, and 10: mean = 20 / 4 = 5, median = 4, and range = 10 - 2 = 8.
Mean, median, and range keep the measurement unit. Order the values before finding the median.
Calculate the requested summary for today's supplied values, then write what it reveals and what it hides.
- • The solution must address the stated need in physiology sensor lab.
- • The decision must be supported by E1-E3.
- • The final product must make the success criteria visible.
- • Complete the work inside the 80-minute block.
- • Use only supplied or teacher-approved materials and evidence.
- • Do not trade , accessibility, or privacy for speed.
- • and evidence quality: must pass before scoring other criteria.
- • User need and effectiveness: highest scored criterion.
- • Time, cost, and ease of use: compare only after and effectiveness pass.
Test evidence: For each option, record the E1-E3 result that supports or fails each criterion. Do not assign a score without a named observation.
- Version or option tested
- Criterion met or missed
- Evidence ID and result
- Revision made
- Reason for the revision
- Need and user
- Criteria and constraints
- Chosen option and evidence
- Test result
- Revision and reason
Students often think Students believe one careful measurement is enough if they were focused and the device looked accurate.. The trap: A single reading cannot show reliability, because you have no way to see the normal trial-to-trial variation, so repeating trials and recording each one separately is what turns a number into evidence.
Research question: Does light activity raise resting heart rate?
Sensor: pulse/heart-rate sensor, calibrated against a 60-second manual pulse count before trial 1.
Conditions controlled: same subject (Subject A), seated for baseline, same room temperature, 2-minute rest between trials.
I recorded five repeated trials for each condition and logged every reading separately rather than averaging in my head:
- Baseline (resting), trials 1-5: 72, 70, 74, 71, 73 bpm
- Treatment (after 1 min stepping), trials 1-5: 96, 99, 94, 101, 98 bpm
Condition-control note: I kept the subject, sensor placement, and rest interval the same across all trials so that the only thing changing was rest vs light activity. That is what lets me trust a difference if I find one.
| Trial | Condition | Heart rate (bpm) |
|---|---|---|
| 1 | Baseline rest | 72 |
| 2 | Baseline rest | 70 |
| 3 | After stepping | 96 |
| 4 | After stepping | 99 |
| 5 | After stepping | 94 |
This model shows the level of evidence and organization needed to complete: Completes the Problem 2 sensor-lab data-collection step: a structured raw data table of repeated, controlled physiology trials ready for analysis.
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.
Also due today: Submit your raw data table on Schoology before leaving the lab area.
- CER:
- Claim, Evidence, Reasoning: make a claim, back it with evidence, explain your reasoning.
- SOP:
- Standard Operating Procedure, the exact steps to follow (especially in a lab).
- Tracker:
- Your PLTW progress log where you record completed evidence.
- myPLTW:
- The PLTW course site where you do the online activities. Find it in Clever with your Microsoft sign-in, right next to Schoology.
Tap the speaker to hear a term. Add two of these to your notebook glossary with a definition and an example in your own words.
Pick just 2 or 3 words from today and make them yours: write what each one means in your own words, name the context clue or evidence that helped, then give one example from what you actually did in Physiology sensor lab. Try your own words first; the glossary is there if you get stuck. This is voluntary and counts as extra credit, so keep it short.
Saved on this device. Show Mr. Mendoza or add these to your notebook glossary to claim the extra credit.
Classroom documents for this lesson are posted in Schoology. Open Clever, then Schoology, and find each one by the name shown on its card.
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:physiology, research design. Score 142. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:physiology, research design. Score 142. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/00_Problem-Overview; keywords:physiology, research design. Score 138. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Sign in to Clever with your district Microsoft account to open Schoology or myPLTW. Follow today's posted steps. If myPLTW will not open, use the posted alternative and tell Mr. Mendoza. Turn in your completed work through the Schoology assignment.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about physiology sensor lab. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Your table shows one baseline heart rate and one exercise heart rate. Your partner says 'that proves exercise raised it.' Why is one trial each not enough, and what fixes it?
Write an answer and pick a confidence to unlock the key.
Fast retrieval with instant answers, not the commit-then-reveal check above. Try each from memory first: write what you remember about the earlier units, then check yourself here.
Missed class or ready for more?▸
Run this before you touch the bench. It is built from the real lab procedure, so the decisions you make here are the ones you will make with the equipment in your hands.
I can name the procedure's purpose and the evidence I will record. I can state today's specific hazards and the control for each. If this deck does not name them, I ask Mr. Mendoza before I touch anything. My data table is ready before materials are handled.
Finish the checklist before you handle any material.
- • Wash hands before placing any sensor on a participant.
- • Do not share sensor components that contact skin without wiping with an alcohol swab between uses.
- • Stop the trial immediately if a participant reports discomfort, dizziness, or pain.
- • Do not collect data on a participant who has not verbally consented for this class activity.
- • Follow the instructor's calibration protocol exactly -- do not skip steps.
- • Store sensor equipment in the labeled case when not in use; report any damage immediately.
- 1Before materials are handled, identify the purpose, variables or comparison, controls, measurement units, and stop-work condition.
- 2Set up the sensor and calibrate it per the protocol.
- 3Record baseline and treatment measurements for each trial.
- 4Repeat trials to capture variation.
- 5Log all readings in a structured data table.
- 6Submit your raw data table.
- 7Record each result in the prepared table before interpreting it. Mark missing, repeated, or invalid results truthfully.
- 8Complete the named cleanup and waste route, remove PPE safely, wash hands when required, and confirm the station is ready for the next group.
| Trial or sample ID | Independent condition | Measured result with units | Observation before interpretation | Quality-control note |
|---|---|---|---|---|
Before the procedure, predict the result and cite the rule behind the prediction.
After the procedure, compare the result with the prediction and name one limitation or source of uncertainty.
What today's skills lead to. These are real health-science careers this course builds toward. Tap one to see, on the US Department of Labor's O*NET site, what the job actually involves, what it pays, and how fast it is growing.
Use a teacher-provided physiology dataset or a PhET simulation to generate readings, then build a structured spreadsheet dataset of repeated trials with labeled conditions.
PhET Interactive SimulationsUse the submission route shown on today's today's page.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
Khan Academy Statistics and Probability- CompleteEvery required part of the artifact is present, nothing left blank.
- AccurateThe science and the data are correct and match the evidence.
- Scientific reasoningYou explain your claim with evidence and reasoning (CER), not just an answer.
- Professional communicationClear, organized, labeled, and written the way a clinician or scientist would.
- SubmittedGo to Schoology to turn this in. Submit one PDF. Put your first and last name in the document header. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
- Error analysis and method · counts doubleName a specific limit of the method and how it moved your result, and compare what you predicted to what happened. "Human error" does not count; say what about the procedure or instrument caused it.
This week
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