ECG Signal Analysis
Budget: $30 – $250 USD
The specific goals of this project are:
1. To apply digital processing techniques to the raw signal (i.e., smoothing, filtering)
2. To compute physiologically relevant, standard metrics from the post-processed data, specifically heartrate (HR) and
heartrate variability (HRV)
3. To develop a hypothesis for a health-related question and use the data to answer that question
4. To interpret your results using basic statistical methods
5. To effectively communicate and present your results in a final report
Deatials:
(1)Standard health data (self-reported metrics) will be collected (examples: gender, age, exercise per week, coffee
consumption).
(2)research a health-related question that could be informed by metrics from the ECG
signal, and at a minimum the computed metrics should include:
a. Calculation of heart rate
b. Calculation of heart rate variability (heart rate variability can be examined in terms of time-based or
frequency-based characteristics)
(3) A large part of the project will be developing your methods for digital signal processing and event detection
(4) Your computed metrics should be applied to ALL PARTICIPANTS FROM THE COHORT (N @ 20) and then summary
statistics developed to test your hypothesis
Report/Submission details:
a. Introduction: introduction should provide an overview of the use of heartrate and heartrate variability to inform health-related illness or disease (this could be generalized but should be based in literature), and a
specific, evidence-based link with these metrics to the health-related question you are asking. You should
also discuss your health-related question, specifically how it has been studied in the literature (or not) with
these metrics and in the population of interest. If you have a hypothesis (for example, “we hypothesize that
females will have increased sympathetic nervous system activity reflected by increased low frequency
signal in the 0.04 – 0.15. Hz band”). ALMOST EVERY SENTENCE IN AN INTRODUCTION SHOULD HAVE An IN
TEXT CITATION AS ALMOST NONE OF THE INTRODUCTION IS YOUR OWN ORIGINAL IDEA.
b. Methods: your methods should include the details of your experiment and provide sufficient detail that
someone could replicate your experiment. This includes the experimental procedure (how many leads,
what type of data were collected, what system was used to collect the data, what did the person do while
data were collected, how many seconds of data were collected, how many people and the characteristics of
that sample); data analysis (what did you do to the raw data, describe any filtering algorithm, the software
used to analyze the data, and how you processed the data to find the metrics of interest); include any
computations (HR, HRV) WITH EQUATIONS, and any statistical methods (ex: averages, standard deviations,
t-tests, correlation, regression).
c. Results: results include the sample statistics (average/standard deviations of age and any metric you
compute/calculate -this could be data we collected such as blood pressure, or metrics that you calculate
such as heart rate), how many male/female participants, the results of your statistical analyses. You should provide summary tables and figures to visually represent your data. Figures and Tables should be labeled
and have captions.
d. Discussion and conclusions: attempt to interpret your data and analysis – does it make sense or support
your hypothesis? Does it support what you found in literature? You should use extensive IN TEXT citations
in this section and refer to your results to support your interpretation but don’t restate your results.
e. References: Include your references in any format you choose. You should be using IN TEXT CITATIONS
THROUGHOUT YOUR REPORT.
1. To apply digital processing techniques to the raw signal (i.e., smoothing, filtering)
2. To compute physiologically relevant, standard metrics from the post-processed data, specifically heartrate (HR) and
heartrate variability (HRV)
3. To develop a hypothesis for a health-related question and use the data to answer that question
4. To interpret your results using basic statistical methods
5. To effectively communicate and present your results in a final report
Deatials:
(1)Standard health data (self-reported metrics) will be collected (examples: gender, age, exercise per week, coffee
consumption).
(2)research a health-related question that could be informed by metrics from the ECG
signal, and at a minimum the computed metrics should include:
a. Calculation of heart rate
b. Calculation of heart rate variability (heart rate variability can be examined in terms of time-based or
frequency-based characteristics)
(3) A large part of the project will be developing your methods for digital signal processing and event detection
(4) Your computed metrics should be applied to ALL PARTICIPANTS FROM THE COHORT (N @ 20) and then summary
statistics developed to test your hypothesis
Report/Submission details:
a. Introduction: introduction should provide an overview of the use of heartrate and heartrate variability to inform health-related illness or disease (this could be generalized but should be based in literature), and a
specific, evidence-based link with these metrics to the health-related question you are asking. You should
also discuss your health-related question, specifically how it has been studied in the literature (or not) with
these metrics and in the population of interest. If you have a hypothesis (for example, “we hypothesize that
females will have increased sympathetic nervous system activity reflected by increased low frequency
signal in the 0.04 – 0.15. Hz band”). ALMOST EVERY SENTENCE IN AN INTRODUCTION SHOULD HAVE An IN
TEXT CITATION AS ALMOST NONE OF THE INTRODUCTION IS YOUR OWN ORIGINAL IDEA.
b. Methods: your methods should include the details of your experiment and provide sufficient detail that
someone could replicate your experiment. This includes the experimental procedure (how many leads,
what type of data were collected, what system was used to collect the data, what did the person do while
data were collected, how many seconds of data were collected, how many people and the characteristics of
that sample); data analysis (what did you do to the raw data, describe any filtering algorithm, the software
used to analyze the data, and how you processed the data to find the metrics of interest); include any
computations (HR, HRV) WITH EQUATIONS, and any statistical methods (ex: averages, standard deviations,
t-tests, correlation, regression).
c. Results: results include the sample statistics (average/standard deviations of age and any metric you
compute/calculate -this could be data we collected such as blood pressure, or metrics that you calculate
such as heart rate), how many male/female participants, the results of your statistical analyses. You should provide summary tables and figures to visually represent your data. Figures and Tables should be labeled
and have captions.
d. Discussion and conclusions: attempt to interpret your data and analysis – does it make sense or support
your hypothesis? Does it support what you found in literature? You should use extensive IN TEXT citations
in this section and refer to your results to support your interpretation but don’t restate your results.
e. References: Include your references in any format you choose. You should be using IN TEXT CITATIONS
THROUGHOUT YOUR REPORT.