INTRODUCTION OF THE QUANTIFIED-SELF MOVEMENT

In today’s world, health is becoming more and more important. More people are paying attention and monitoring their health to gauge change and trends. The Quatified Self Movement is something that known as lifelogging. It ultilizes modern technologies such as wearables in terms of data acquisition such as calories intake, calories consumptions, steps, distances, as well as a person’s performance or mental states by gauging his or her heart rate, EKG, oxygen intake, blood pressure, VO2, the Quantified Self allows regular person to track and study his or her life with easily-accessible technologies. ***

DATA COLLECTION & PREPARATION

For this project, I choose to use the data from my Apple Watch and my iPhone; since both the Apple Watch and iPhone are with me throughout the days and they collected all data on a daily basis. Datas that will be used including Distances(mi), Steps, Heart Rate, and Minutes in Bed (Sleep Time). The date range for Heart Rate is from Janurary 29th 2019 to Feburary 18th 2019 because Apple Watch was acquired recently. The date range for rest of datas is from November 18th 2018 to Feburary 18th 2019

I will be looking into answering the following questions: 1. What is my walking/running distance on a weekly or monthly basis? 2. Is there a correlation between my steps taken and heart rate? 3. How’s my sleep? 4. How does my walking/running distance affected by day of the week? 5. What’s my cumulative distance for the date range?

Q1: What is my cumulative walking/running distance for the given date range?

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.1092  1.4482  2.5796  2.9238  3.8301  7.8042 

*** As seen from the graph, it appears that most of the distance fall under 5 miles, while only two occurance supassed 7.5 miles mark.

Q2: Is there a correlation between my steps taken and heart rate?

*** Based on this graph, I was surprised see that sometimes that my heart rate went above average despite the fact that step conts were not above average around the same time period.

Q3: How’s my sleep?

 Sleep..In.bed.start. Sleep..Minutes.in.bed.  Hours in Bed  
 Length:78            Min.   : 17.21         Min.   :0.300  
 Class :character     1st Qu.:379.57         1st Qu.:6.325  
 Mode  :character     Median :423.51         Median :7.100  
                      Mean   :367.09         Mean   :6.112  
                      3rd Qu.:440.51         3rd Qu.:7.300  
                      Max.   :470.00         Max.   :7.800  
      Date              Weekday         
 Min.   :2018-11-18   Length:78         
 1st Qu.:2018-12-07   Class :character  
 Median :2018-12-26   Mode  :character  
 Mean   :2018-12-27                     
 3rd Qu.:2019-01-14                     
 Max.   :2019-02-19                     

*** It appears that most of my sleeps are over 7 hours, but just under 8 hours. I think that’s enough, who needs 8 hours sleep anyway :). And it seems that Saturday is the day with most hours in bed, and Friday and Monday are the least ones.

Q4: How does my walking/running distance affected by day of the week?

*** Based on this data, I am surprised to see that I tend to walk the most on Wednesday, Monday is the day I tend to walk the least. And I should move more on the weekends as well.

Q5: Is there a correlation between my sleep hours and distance?

*** No particular trend is spotted here, nevertheless, it apeears that the 3rd quartile distance of 3.83 miles seems to correlate with the 3rd quartile of sleep hours which is 7.3 hrs.

CONCLUSION

According to the visualization, the following conclusion can be drawn, 1. Weekdays tend to be more active than Weekends. 2. Satuday has most sleep hours, Friday and Monday having least sleep hours. 3. No particular correlation observed among sleep hours, distance, and step counts. 4. I should move more often

Thnak you.