Case Study Analysis
Instructions:
1. For each individual, determine their predicted maximal oxygen uptake from the YMCA test results and complete the exercise prescription based on these results.
2. For each individual, compile data into a one page typed sheet assessing their physical fitness as well as their resting HR/BP, and BMI.
3. Include a description of what the YMCA test evaluates and the importance of this test. Include numbers and classifications/percentiles for your findings.
4. The 1-2 page document that you create should be formatted as an informational handout that you will be giving the individual to summarize their results. Therefore, you must make it easy to read and interpret and should only include pertinent values (e.g. VO2, HR, BP, BMI). Focus on quality vs quantity of what is written.
5. The last portion of each document must include the distinct exercise prescription that you calculated for this individual (both moderate and vigorous intensity).
Case Study Grading Structure:
Accurate Calculation/Assessment of Each Test: 5 points
- Ensure numbers (e.g. VO2, HR/BP, BMI) and classifications/percentiles are correct.
Clear and Comprehensive Evaluation and Description of Results: 5 points
- Test description included and can be clearly interpreted
- Ensure it is easy for the reader to see and interpret their results
- Clear exercise prescription structure and values
YMCA Submaximal Cycle Ergometer Test Data Form
Subject: Johnny
Date: 10/19/2020
Age: 55 yr
Gender: Male
Weight: 170 lbs.
Height: 70 inches
Resting HR: 80 bpm
Resting BP: 120/80 mmHg
Seat Height: 5
Min Stage Work rate (kpm/min-1) HR (bpm) BP (mmHg) RPE Comments
1 I
150
2 105
3 105 130/80 10
1 II 300
2 115
3 115 140/85 12
1 III 450
2 140 150/80 15
3 140
IV
Moderate Intensity Vigorous Intensity
Frequency – Frequency –
Intensity – Intensity –
VO2 Reserve Method (VO2R): VO2 Reserve Method (VO2R):
Duration – Duration –
YMCA Submaximal Cycle Ergometer Test Data Form
Subject: Moira
Date: 10/19/2020
Age: 60 yr
Gender: Female
Weight: 125 lbs.
Height: 62 inches
Resting HR: 70 bpm
Resting BP: 125/75 mmHg
Seat Height: 5
Min Stage Work rate (kpm/min-1) HR (bpm) BP (mmHg) RPE Comments
1 I
150
2 95
3 95 130/75 11
1 II 450
2 110
3 120 140/65 13
120
1 III 600
2 140
3 150 155/70 15
4 150
IV
Aerobic Exercise Prescription
Moderate Intensity Vigorous Intensity
Frequency – Frequency –
Intensity – Intensity –
VO2 Reserve Method (VO2R): VO2 Reserve Method (VO2R):
Duration – Duration –
Sample Solution
he goal is to segment a movie into shots and to select a representative key frame from each shot. IBM’s Multimedia Analysis and Retrieval System (IMARS) (Natsev, Smith, Tešié, Xie, & Yan, 2008) will be used for shot boundary detection. Since a key frame can represent a shot, the middle frame from each shot will be extracted as key frame for visual analysis.
3.1.2 Feature Extraction
Given the segmented clips, features are extracted in terms of actor appearance, genre, and visual descriptors.
Actor appearance
Actors are key to a consumer’s expectations of the movie. A good personalized trailer would feature those actors that are most relevant to a user’s interests. To recognize these actors, the easiest way is to use face recognition. A face recognition system using Eigenfaces (Turk & Pentland, 1991) will be implemented in OpenCV . Facial recognition using Eigenfaces promises great recognition accuracy of around 95% (Kannan et al., 2015).
Genre
Specific movie events can correspond to genres, i.e., a romantic shot in a movie should be classified as belonging to the romance genre, so that it is more likely to be recommended to someone who prefers romantic movies. These movie events are to be manually annotated for each shot as they cannot be automatically detected even using the most modern semantic concept detection methodologies (Kannan et al., 2015). This is because of the highly subjective nature of these movie events, and because “the low-level visual features trained for classificatio