Passengers Visit 1 and 2

“Passengers”

Wow, this has been a while. Silence means not inactivity. So I’d like to give you some updates right now. I will start with this great movie “Passengers” by the Norwegian Morten Tyldum (director) and Jon Spaihts (writer) from 2016. To my extend this is a new landmark for future design and an example of dedicated craftsmanship in script writing. A limited cast with a great dilemma in existential scale. It has been a pleasure to be a part time space (and time) traveller while watching this movie with its superior production design. Guy Hendrix Dyas work is nominated for the Oscar 2017. He better be!

I’ve been accompanied by 15 students of mine – they’ve been willing to give me their heart rate in exchange for the ticket. It was a kind of semester goodby as well. Their results are not yet evaluated. The raw data looks very mixed, as always.

Passengers Sessions in Movie Pulse
Some of the multiple recordings – raw and not yet synced

But because I’ve seen the movie twice, I’ve been curious to compare my first and second visit of the same movie. I felt very strong body reactions because of certain story incidents, as well as from the brillant sound. Did I mentioned the audio? Wow, terrific! I found an insight of the work of Will Files – one of the gifted audio folks involved.

A short look at both graphs made available through my app Movie Pulse obviously confirmed my presumption. But that even the high and low peaks at the end match 100% is definitely by chance. I combined both graphs for better comparison.

Passengers Visit 1 and 2
The impact after 1 hour has even been higher at the 2nd screening.

Since I do not yet have the movie available on DVD or Bluray I can only guess what happened after 1 hour. I am pretty sure that this has been caused by a simply two line dialogue, because at the 2nd screening I knew instantly that these en passant spoken words will have serious consequences. As I write these lines: what if not? Let’s see later, if the movie is available. Come on, it’s an assumption, can be proven wrong…

Jim: There’s no secrets between us.
Arthur: Is that the case?

Michael Sheen
Michael Sheen as “Arthur” the android barkeeper

Because I have access to the raw data of the recordings on my research devices (which is not [yet] available at the official app at iTunes, because of privacy rules), I can get my hands on the data curves. I made two graphs, comparing both recordings. As always the data is now basis 0 at the average heart rate and normalized.

Curves of both cinema visits
Both curves compared show areas of very similar reaction of the test person (me)
Conformity in red an green
Time line to compare both movie screenings: green areas depict similar reactions, red ones show the timespan which differentiates

There are a bunch of movies with a horseload of data waiting to be analyzed and evaluated. Among them the heart rates of 15 people watching this movie. Let’s see if I can find some more conformity comparing those, rather than my own visits. Dr. André Weinreich and me are almost done with the sessions in this semester. I will give you a follow up what happened the last months.

"Avakenings" 1990 by Penny Marshall · Normalized raw data - not analyzed yet

New Research Partner · Summer Break

I am very happy about our new very interesting research connection: Dr. André Weinreich, Head of Research & Science from emolyzr (DE) is joining our Movie Pulse research group. He is a psychologist and dedicated researcher of emotions. His particular interest to join is the supposed ability to find emotionial patterns in peoples reactions, while watching movies  – with the help of our app. This would be a breakthrough, because the app frees the research process from the need of a lab (within the limits of data which can beachieved with a wearable, of course). You can find more about their very sophisticated approach if you watch the videos of this company, which has been founded by the Humboldt University, Berlin.

Although some more data is waiting to be analyzed – we will now have our holiday break. Enjoy your days of lazyness or activity…

We will continue to analyze already recorded data, as well as we will run new screenings. I am especially keen to see the results of “Awakenings” 1990 by Penny Marshall – one of the most emotionial movies I’ve ever seen.

"Avakenings" 1990 by Penny Marshall · Normalized raw data - not analyzed yet
“Awakenings” 1990 by Penny Marshall · Average raw & normalized – not yet analyzed

“Room”

I have to admit that I am currently running out of time for watching movies. But a friend helped me out with an impressive movie pulse of “Room” by the Irish Filmmaker Lenny Abrahamson. Brie Larson won the Oscar for her Joy “Ma” Newsome character.

“Room” by Lars Abrahamson, 2015

See by yourself: this is a awesome steady increase- I have never seen something like this before.

I am so curious what kind of story caused this almost symmetrical climax?

My habits on movies are quite special: I avoid to know anything beforehand and just mark a movie “worth watching”, after I picked something here and there. I’m quite sure I will still find a cinema in Berlin playing this movie, it’s on top of my list now!  I won’t even watch the trailer – you may…

Consider sending me your movie pulse after watching this (or any other) movie, since the fun part is comparing.

“Room” by Lenny Abrahamson, Trailer

The Nice Guys · Shane Black 2016

“The Nice Guys”

I am quite busy because of improving my analyzing tool set for multiple records. Spreadheet analysis with charts, graphs, normalization,  gender, age, formulas and stuff. A hell of a lot of data to process. This will keep me busy probably for the next weeks.

But sometimes I am able to reserve some spare time to watch a movie – like “The Nice Guys” by Shane Black which is a really entertaining piece of flick. Steady increasing heart rate – like the joy I had watching it. To guys going goon: Ryan Gosling as the stupid goon and Russell Crowe as the one with the loose fists. Watch those guys in this quite hilarious circumstances yourself. Before it’s to late.

 

The Rocky Horror Picture Show seen by five study volunteers

“The Rocky Horror Picture Show” · Lecture Record #3

This has been the most “shocking” movie for my students so far. At least three of them could not stand it’s b-movieish style, story and characters. But most of them watched it completely and some of them had have fun. But I assume this has been the minority. The concept of the movie will not work nowadays: to board a loved genre of the former generation (musical) and to whisk contemporary no-no’s, controversial moral issues and sexual frankness into a hym of individuality. My subjective appraisal on this consists of two motivations: 1st – this is not their music, therefore it’s just another musical for them; 2nd – society tends to prefer conservative ideas at present, even the younger are part of this trend. The sexual individuality and freedom of personal choice is still not guaranteed – even 41 years! after RHPS has been released.

We still have not achieved absolute pleasure.

Little Conformity

Although this is still not a valid test scenario in terms of quantity – I’d like to apply the former developed strategies for data comparison to this little data set again. This will help to achieve a valid outcome on a later larger scale of study volunteers.

The Rocky Horror Picture Show · Amount of aberration
The amount of aberration has been quite massive (light grey) and the less than average aberration little (dark grey)

Compared to former records this movie has raised very divers reactions and a small amount of similar tendencies. Just to recall: high values of the light grey depict regions where the subjects tend to have no comparable heart rate. The dark grey regions show the time spans of more similar reactions.

The Rocky Horror Picture Show · Accordance of 100%
Accordance of 100% percentage in red, calculated average in grey.

The absolute identical reactions of alle participants in terms of above or below the base line therefore have been very short and few (8,9 %).

Majority will make the Difference

The Rocky Horror Picture Show · Accordance of majority
The accordance of the majority (3 out of 5) compared with 100% accordance (black)

Five participants can have a majority of 60%. So 3 out of 5 show more similar reactions in high pulse (red) and low pulse (green). The 100% accordance is included in black, since this is a subset of the majority calculation.

Gender Comparison

The Rocky Horror Picture Show · Comparison of gender accordance
Comparison of gender accordance (male blue and female orange)

This comparison is new – almost new. I used it in “The Angry Birds Movie” to differentiate between the parent and the children reactions. I will make this a standard comparison: building subset groups of the study volunteers – the most obvious is gender. As long as we will have a fifty-fifty arrangement. And of course: this is only a valid result, if based on a relevant group size. Having 2 female and 3 male will not really suffice. But for building the tool set, we’ll use it for now. 54,4% of the female and only 28,7% of the male have had identical reactions within their group.

The Rocky Horror Picture Show · Gender difference and accordance
Accordance of all study volunteers (green) and regions where female and male reacted differently compared to the other gender (red)

This will improve the depicting of the differences for sub group comparison: you can easily compare the green amount of the movie, which caused similar reactions on all participants (8,9 %), with the amount of differences between the two groups: red shows the parts (51,7%) where female and male reacted similar within their own group (sex), but different to the other gender.

Visualization

The video depicts again the average threshold of the majority (60% this time) – the image becomes tinted in green and red. To make this work more obvious I have destained the movie beforehand. Additionally the 100% subset of all four test users has been included as well. To distinguish both data visually, a hint for the 100% subset has been added in white. If one image shows a white frame: this means all viewers have reacted the same way, not only the majority. The graph below the timeline shows this subset in white as well.

Additional design options for the resulting graph

Version 1.1

Thanks for coming up with your suggestions. I was able to make the usabilty more comfortable and save to prevent chances of faulty operation.

Improved design and usability for iOS and WatchOS.

  • several bug fixes
  • separate record tab to handle multiple records
  • supporting multiple watches
  • additional design options for the resulting graph
Version 1.1 · Portrait
Version 1.1 · Portrait
Additional design options for the resulting graph
Additional design options for the resulting graph
"The Angry Birds Movie" · A Family Record

“The Angry Birds Movie” · A Family Record

We had a long awaited trip to the cinema with our two boys, age 6 the little and the older one became 8 years old just recently. They have watched so many Angry Birds Shorts and now wanted to see the feature movie. When I asked them why, they could not really state more than “it’s fun”. I’ve read a very short review stating it’s a sequence of gags only. Not a good starting point for parents.

But to make an ease start: we’ve had fun watching it. Recording the pulses of all family members had brought some prove that these kind of movies are build on two major layers (if we disregard the fact that we four are not a qualified test screening quantity).

I won’t go into detail on the movie itself. It’s a merely simple world and characters, compared to “Zootopia” for example. But the richness of references to contemporary and history of media has a certain quality. We, the parents, had often laughed out loud: Terence can be seen as a revenant of Chief Bromden from One Flew Over the Cuckoo’s Nest” and you can meet the female twins of “Shining” as well as you can party with Daft Punk. Not to mention that Rick Astley’s “Never Gonna Give You Up” will be played at a central moment for the (former) hero Mighty Eagle. And the main character Red has a interesting personality and a goal; presumably this movie has a story after all.

100% accordance (green) · 100% accordance of the parents (grey) · 100% accordance of the childs (blue) · discrepancy of parents vs. childs (red)
This is my major outcome of inspecting the results of the Family Record: red
depicts the time children and parents reacted different while watching the movieThe following steps will explain how this result has been achieved. If you’re not familiar with the workflow I developed so far, I recommend reading the “Citizen Kane” post first, because I’d like to refer to some steps with not going into detail again.

All four records stored in the Movie Pulse app
All four records stored in the Movie Pulse app

All records as relative values on their main average, which refers as base zero.
All records as relative values on their main average, which refers as base zero
All of the four records of the family members are changed to relative values, based on their single average. Parents records have a warm color, the records of the children are shown in cold tones.

The aberration of all family members (light grey). Higher values show greater discrepance. Dark grey depict areas of less than average aberration.
The aberration of all family members (light grey) and less than average aberration (dark grey)
Higher values show greater discrepancy. Dark grey depict areas of less than average aberration, which means the majority of viewers tend to have the same reactions, either above or below their main average.

Accordance of 100% percentage in red, calculated average in grey.
Accordance of 100% percentage in red, calculated average in grey.
The red line shows the moments of the film when the complete family has reacted in the same manner: all four have had either a raised pulse above zero, or had have a calm pulse below zero. The amount of accordance over time is 17,6%. But I now start a little clustering and interpretation.

The accordance of the majority (3 out of 4) compared with 100% accordance (black)
The accordance of the majority (3 out of 4) compared with 100% accordance (black)
As I stated in the beginning: I refer to the same procedure I developed for “Citizen Kane”: besides the finding of 100% accordance, I am looking for the areas of conformity of the majority of viewers (3 out of 4). This shows a greater pattern of resemblance over time: a high result of 68%!

But this time I will try something new: I’d like to match the differences of the children’s outcome with those of the parents!

The results are divided into the subcategories “Parents” and “Childs” and their results are computed separately. This proofed the idea that watching “The Angry Birds Movie” triggered both groups in different ways.

100% accordance (green) · 100% accordance of the parents (grey) · 100% accordance of the childs (blue) · discrepancy of parents vs. childs (red)
100% accordance
 ·100% accordance of the parents ·100% accordance of the children ·discrepancy of parents vs. childrenThe green row is the result we’ve had in different styles beforehand: 100% accordance (17,6 %) of all family members. Grey is used to mark the timespan when both parents reacted similar (astonishing 57,3%), blue shows the conformity of both boys (an even higher result of 58,8%) and finally red discloses disparity between the parents and children’s reactions (50,4%).

Citizen Kane · Orson Welles · 1941, Watched and recorded with 4 test persons

“Citizen Kane” · Lecture Record #2

We are one step closer to our general aim. For identifying structures within movies we analyze the heart rate of the viewers with our Movie Pulse app. Because of a generous support we’re now able to record up to 5 viewers in parallel! For a first start with multiple Apple Watches we’ve had four volunteers watching “Citizen Kane”. All Watches are paired to a single iPhone 5 and committed their data without any hassle. The data shows no gaps, missing periods of recording. Only a small exception of being perfect: one record stopped prior the end of the movie. Perhaps the user inadvertently pressed the stop-button. Therefore the last 13 minutes are not having the base of 4 recordings and are less significant.

Having watched “Citizen Kane” is an important requirement in terms of understanding the history of cinema. That motion pictures are able to condense what went wrong in an entire single life with a single ordinary object – this really strikes me every time I see this movie. I don’t want to go into details here. “Rosebud” is all I have to cite.

Raw data of four test persons watching "Citizen Kane" the same time
Raw data of four test persons watching “Citizen Kane” the same time

If we now have a look onto the raw data of our Movie Pulse volunteers – my first reaction has probably been the same than yours: Am I on the right track? For heaven’s sake, how could this mess matter in any meaning?

They all must have seen another movie or the whole Movie Pulse enchilada is for the birds. Wait. The data needed some nurture.

Absolute figures are nonsense

We need to have a look at each recording individually. Each person has his/her own resting heart rate. We don’t know this rate, but we can calculate the overall average for the movie records of this person. This figure along with the minimum and maximum pulse in this period of time is the starting point of all our computations. In the Movie Pulse app there is a far more sophisticated algorithm which computes not only the overall average, but the average changing within a specific time frame. This gives the nice up and down trend line. Having here the plain average will be sufficient for now.

The same data all vertical aligned at their average. Note the absence of absolute figures of the heart rate.
The same data vertical aligned at their average. Note the absence of absolute figures of the heart rate. The colors have been altered to a warm tone for female, cold for male test users.

Adjust the base

What formerly has been the average will now serve as the base – zero null. The numbers of units from average to the lowest will represent the minimum range of units the person has reached. The maximum units are defined the same way above zero. Instead of having a heart rate, we deal with a range of units at a base of zero – the threshold of maximum and minimum our test person has reached at a particular time within the movie.

Amount of deviation

A first attempt is to identify the amount of difference at each recording time. Let’s say at time 0:32:12 person 1 has a value of 4, person 2 a value of 6, person 3 a value of 7 and person 4 a value of minus 4. Three people are above their individual average and one person is below it. The deviation is 4,43…. somehow complicated, therefore computers come in very handy. Two more simple examples: p1 value 1, p2 value 1, p3 value 1 and p4 value 2 will have a deviation of 0,5. Yes 1,1,1,1 will gain 0,0 – no difference at all. Low deviation will mean great conformity – which, in our analysis, is the biggest proof of having viewers responding similar.

Determining the deviation compares the data and will give a guidance: low deviation means users reacted more similar.
Determining the deviation compares the data and will give a guidance: low deviation means users reacted more similar.

To make this graph more readable I added a simple TRUE value for those recordings which have a small deviation (average or below), which is represented by the darker gray. This is a first hint for periods of time which have gained equal reactions.

Direction is all we need

But there is one problem: How about the differences the test users have in terms of range of threshold? Of course, according to my theory, a very high or low value will state either high attention or intense state of being calm. But this is the peak we might come closer soon; for now it’s more elementary and useful at which moments the viewers responded in the same way, the same direction!

The simple overall average of all records is depicted in grey. The red line shows the period of time all four users had have data within the similar area: either above or below their own zero base.
The simple overall average of all records is depicted in grey. The red line shows the period of time all four users had have data within the similar area: either above or below their own zero base.

I came to the conclusion that having an overall average of all four users might not sufficient and will alter the data in a wrong way: Imagine one person reacting completely different. With pure math average his or her data will be taken into account nevertheless it might be completely different than the majority. This is what we’re after: majority.

The resulting graph shows data where the majority (three out of four, 75%) has had similar data either above (red) or below (green) the zero base. 100 % similarity is shown in black.
The resulting graph shows data where the majority (three out of four, 75%) has had similar data, either above (red) or below (green) the zero base. 100 % similarity is shown in black.

For this reason I computed the graph depicting the average raise or descent of A) all four test persons B) of the majority of 75% of the test persons which is shown in red and green. Therefore A) is a subset of B) and is marked in black on this image (white in the video).

Again the movie is boiled down into 2 minutes excepts, placed beside each other; one row representing 30 minutes of the movie.

Those 100% and 75% conformity results have been used in the “Citizen Kane in 2 minutes” movie. The overlay of green and red color is applied at the same rules as the prior published “Metropolis in 2 minutes”: high units above the average will tint the image in red, low units in green. This time the color is multiplied with the image, not overlayed.

The video takes the average threshold of the majority (75%) into account – again the image becomes tinted in green and red. Additionally the 100% subset of all four test users has been included as well. To distinguish both data visually, a hint for the 100% subset has been added in white. If one image shows a white frame: this means all viewers have reacted the same way, not only the majority. The graph below the timeline shows this subset in white as well.

Please remember that this first multiple recording unfortunately is not complete approx. 13 minutes prior the movie ended. So “n” has changed from four to three persons at 1:39:12. There is always room for improvement. Any sugestions are welcome too! 

Metropolis · Fritz Lang · 1927

“Metropolis” · Lecture Record #1

This time I’d like to start to refer to movies which are important in film history and have a certain age. “Metropolis” is the mother of science fiction – besides the Georges Méliès Le voyage dans la lune” (1902!). Numerous experts have already debated about it’s value, impact and whatsoever outcome in vision, theme and cinematic morphology. One thing I find interesting myself is the fact that the author Thea van Harbou has had a different aim than the director Fritz Lang: I remember a statement on the extras of the restored version of Enno Patalas – Lang was mainly fond of the human-machine setting; of machines in general, whereas van Harbou focused the idealistic approach that the heart has a mediator function between hands and the mind.

Metropolis · Fritz Lang · 1927
Metropolis · Fritz Lang · 1927

I showed this movie to my students and picked a random volunteer wearing the Apple Watch for running Movie Pulse for the length of the film.

Again: this is a individual result and can not validate the general impact of the movie.

But beside watching and exploring heart rates of movies myself, giving lectures, thinking of app improvements and features, raising comparable results of the same movie –  I think it’s quite important to achieve some visual experiments on depicting the heart rate graph along with the movie itself. Without legal infringements.

A timeline of "Metropolis" along with the Movie Pulse result of a volunteer.
“Metropolis” timeline along with the Movie Pulse result of a volunteer. (Click to enlarge)

This approach seems very inefficient, besides the less detailed graph and the quite small images. So why not combining the result with the movie itself?

  1. combine the heart rate with the images of the movie
  2. doing this for the length of the movie
  3. depict the change of beeing calm/exited
  4. provide an overview

Those ideas led to the 2 minute movie you can see here:

Example: Finding the sequence at 0:39
1st row = 30 minutes + 2nd row 5th image = minute 0:38 – 0:40

Each row shows 30 minutes of the movie. 2 minutes excerpts are placed side by side, so 15 excerpts are depicting 30 minutes, 4 rows showing the almost 2 hours. The graph below the images is just an orientation – since the green and red tint has been rendered slightly different. I determined an overall average – this refers as base zero for red and green. The max value yields 100 % red, min value provides as 100% green.