Research Session · Analysis 1.0

Accompanied by Dr. André Weinreich, Head of Research & Science from emolyzr/Humboldt University, I’ve run several sessions during the winter semester 2016/17. We now have a gathered some data for the movies which had have enough attendees.

The numerical data provides two main starting points: either analysing the questionaire or the plain heart rate data. We check several options to find some correlations between them. The first obvious result is the relation of mean heart rate and liking. At present we focus on cluster analyses from both “ends”: the average rating as well as the individual pulse.

These are the mean heart rates of each screened movie in alphabetical order. In this earlier post some reasons are given, why these films were chosen. Most movies have been screened in a lecture hall, some at a regular cinema, which clearly caused immersiveness at different levels.

Some clues to read the data:

  • Have a look which approx. mean heart rate the movie evokes
  • Watch for immediate changes (up or down)
  • Look for sections which continously differ from mean heart rate
  • The dynamic range, the film has caused in general, is an indicator as well
  • Can an overall trend be identified in individual sections or the entire film?

American Psycho

Mary Harron · 2000 · n=16 (Berlin, Lecture Hall)

American Psycho Poster

American Psycho Graph


Penny Marshall · 1990 · n=16 (Lemgo), n=14 (Berlin) both Lecture Hall

Awakenings Poster

Awakenings Graph


Tim Miller · 2016 · n=16 (Lemgo, Lecture Hall)

Deadpool Poster

Deadpool Graph


Jean-Pierre Jeunet & Marc Caro · 1991 · n=14 (Lemgo), n=16 (Berlin) both Lecture Hall

Delicatessen Poster

Delicatessen graph HR mean

Doctor Strange

Scott Derrickson · 2016 · n=16 (Lemgo, Cinema)

Doctor Strange Poster

Dr Strange Graph

Fantastic Beasts and where to Find Them

David Yates · 2016 · n=15 (Lemgo, Cinema)

Fantastic Beasts … Poster

Fantastic Beasts Graph

Gone Girl

David Fincer · 2014 · n=15 (Berlin, Lecture Hall)

Gone Girl Poster

Gone Girl Graph


Dietrich Brüggemann · 2015 · n=16 (Berlin, Lecture Hall)

Heil Poster

Heil Graph


Spike Jonze · 2013 · n=15 (Berlin, Lecture Hall)

Her Poster

Her Graph

Labor Day

Jason Reitman · 2013 · n=16 (Berlin, Lecture Hall)

Labor Day Poster

Labor Day Graph


Brian Helgeland · 2015 · n=16 (Lemgo, Lecture Hall)

Legend Poster

Legend Graph


Morten Tyldum · 2016 · n=14 (Lemgo, Cinema)

Passengers Poster

Passengers Graph


José Padilha · 2014 · n=10 (Lemgo), n=16 (Berlin) both Lecture Hall

Robocop Poster

Robocop Graph

Schönefeld Boulevard

Sylke Enders · 2014 · n=15 (Berlin, Lecture Hall)

Schönefeld Boulevard Poster

Schoenefeld Boulevard Graph


Maximilian Erlenwein · 2014 · n=15 (Berlin, Lecture Hall)

Stereo Poster

Stereo Graph


Byron Howard/Rich Moore · 2016 · n=14 (Lemgo, Lecture Hall)

Zootopia Poster

Zoomania Graph

The analysis’ goal is to find some structure in observing the heart rate of movie goers. One outcome might be the relation between the heart rate and the likness. Because we are still in the process of applying different approaches, we are not yet ready to publish the whole data.

If you are interested to get more details of this movie analysis study, it’s progress in analysis, or how Movie Pulse can be used for analyzing any feature length movie yourself, get in touch.

Life Poster · Excerpt

Life 2017 · Brazil vs. Germany

The brazilian student G.N. has send me his first Movie Pulse result: “Life” of Daniel Espinosa. This movie has been a solid outer space science fiction to me, whose crew experience felt quite intense. I’ve literally been part of their crew.

I reject the “Alien-alike” bashing of this movie. It had a serious impact to me – encounter a life form of this aftermath combined with it’s inconspicuous appearance.

But this is it so far on discussing the (subjective) quality – I tend to show some nice similarities across oceans, borders and time. G.N. and me have had some strong identical reactions while watching this movie. I made again a simple image multiplication and only shifted the base line. The first two thirds are somewhat ok, but the reactions at the last 30/40 minutes are almost identical. Shifting the base line for each third would have unfold more similarities even within the first hour.

Two people of different origin and age watching "Life" · 2017 at different locations and dates.
The overlapping represents similar reactions of two people of different origin and age watching “Life” · 2017 at different locations and dates.

These are the original graphs drawn by Movie Pulse.

The brazilian record
The Brazilian record
The german (my) record
The German (my) record
Message from OMDb

Movie search currently unavailable

The Open Movie Database (OMDb) is currently under fire by some honks. Therefore finding a movie with Movie Pulse after recording will fail at present. Please keep records at “Unsaved Records”, note the title & date and try again later. You can check the OMDb availability status here.

Message from OMDb
This is what Brian Fritz from OMDb ist telling (4th of February 2017)
Movie Pulse at the cinema

The 2016/17 Research Sessions

Accompanied by Dr. André Weinreich, Head of Research & Science from emolyzr/Humboldt University, I’ve run several sessions during the winter semester 2016/17. We had up to two groups each week – one at the University Ostwestfalen-Lippe in Lemgo, the second at Humboldt University, Berlin. André Weinreich is a psychologist and researcher of emotions. He instantly understood what I am after, to examine the recorded heart rate of movie goers and he urged me to collect data on a broad variation of movie genres. We have two more movies left, but I’d like to compile the list of the recent movies.

The data is about to be analyzed – which will keep us busy the next months.

We probably release some insights from time to time, but please be patient for the proven outcome. Nevertheless I am still working on Movie Pulse as a tool useful for movie maniacs. I have a certain feature in mind for the next major release, but you’re always welcome to send ideas, feature requests and of course report malfunctions.

Autumn/Winter 2016/17 · Research Sessions

  • The Tin Drum, Volker Schlöndorff · 1979
    n=14 (Lemgo)

This story is based on a novel which is freely inspired by historical events. I know this is the most controversy movie I show in my lessons, because students of several years told me. It has been chosen because it evokes disgust as well as sexual stimulation (among other other things, of course).

  • Awakenings · Penny Marshall · 1990
    n=16 (Lemgo), n=14 (Berlin) both Lecture Hall

A drama with the focus on the relationship of a doctor and one of his patients, based on real events. This has been the movie I cried the most in my whole life. It has been chosen because of it’s emotional power to evoke compassion as well as it comes with a particular humor.

  • Delicatessen, Jean-Pierre Jeunet & Marc Caro · 1991
    n=14 (Lemgo), n=16 (Berlin) both Lecture Hall

A caretaker is threatened by the household. Although a bit outdated in terms of it’s fantastic and dystopian filmic universe, the movie is a classic and has been a boiler plate for a series of these kind of movies. It’s part of the screening because of a provocative story, an imminent bad ending and hilarious comedy.

  • Doctor Strange, Scott Derrickson · 2016
    n=16 (Lemgo, Cinema)

A mainstream movie, based on the Marvel comic universe with a favorable actor. Part of the list because of the absence of real human being living condition to identify with, as well as the presence of FX in visual and audio terms.

  • Legend, Brian Helgeland · 2015
    n=16 (Lemgo, Lecture Hall)

Based on the life of two real brothers, this movie brings two important things: an impressive performance of a famous actor (playing adult twins) along with an incredible story. Chosen because of it’s intensity of character presence, conflict and brutality.

  • Her, Spike Jonze · 2013
    n=15 (Berlin, Lecture Hall)

An intellectual movie facing a near future we might have with our smart devices. The movie develops an relationship between the main character and a machine. The scale of emotional involvement of the audience in this artificial plot setup makes this movie interesting for the list.

  • Phantastic Beasts and where to Find Them, David Yates · 2016
    n=15 (Lemgo, Cinema)

A movie based on the proven success of an existing phantasmagorial filmic universe. It deals with conflicts of characters of a non-contemporary plot, fantastic creatures and audio-visual impression. It has been chosen because of the probably lesser character identification, but larger impact in visual and sound terms.

  • Gone Girl, David Fincer · 2014
    n=15 (Berlin, Lecture Hall)

Based on a major conflict a couple has to deal with, the story heads towards classic changes in character judgement by the audience. This movie delivers a focus on the compassion the audience might have with the male or female – without being distracted by visual effects.

  • Robocop, José Padilha · 2014
    n=10 (Lemgo), n=16 (Berlin) both Lecture Hall

The dystopian Science Fiction settled on Earth in some near future re-interprets the successful original from 1987. The movie contains threatening cutting edge technology as well as the misfortune of a human being. Both made this movie useful for the list: the massive audiovisual impact of FX and the sympathy with the main character.

  • Deadpool, Tim Miller · 2016
    n=16 (Lemgo, Lecture Hall)

Based on another Marvel comic character, this movie provides a cynical, obscene and hilarious hero and a classic hero arc. This movie has been chosen because of it’s classical plot, hilarious comedy elements as well as it’s controversial character.

  • Schönefeld Boulevard, Sylke Enders · 2014
    n=15 (Berlin, Lecture Hall)

A female misfit character reclaims her acceptance within her adolescence development. A movie dealing with down-to-earth real problems of a young woman in a contemporary time frame and a ordinary setting. The absence of larger than life plot construction (and production scale) makes this movie of use for the list. How will this affect the compassion ability of the audience?

  • Zootopia, Byron Howard/Rich Moore · 2016
    n=14 (Lemgo, Lecture Hall)

A weak character by definition (bunny) in a classical zero to hero (animation) movie. How will the animated characters move the emotions of the audience? Will the movie provide an immersive experience similar to non-animated movies? These are some main questions we might have analyzing it.

  • Stereo, Maximilian Erlenwein · 2014
    n=15 (Berlin, Lecture Hall)

Preceding events of the life of the main character are affecting the love to a woman. The movie comes with a realistic setting along with a kind of psychedelic split-person threat. How does the audience deals with the psychic harassment as well as with the imminence through physical brutality will make this movie of use for us.

  • Heil, Dietrich Brüggemann · 2015
    n=16 (Berlin, Lecture Hall)

Besides it’s humorous handling of (German) nationalism, the movie has an intellectual quality while offering jokes on all kind of institutions, social levels as well as media formats. The questions for the study can contain the following: How does the controversial topic, the hilarious exposure of quite all characters and the quick succession of jokes will affect the audience?

  • Labor Day, Jason Reitman · 2013
    n=16 (Berlin, Lecture Hall)

A unpredictable character intrudes the life of a single mother with light force. A drama as well as a love story does the movie provide a strong quality of sympathy for all three main characters: intruder, mother and son. Besides the grade of identification with the personell will (presumably) the predictable and imminent end provide strong emotional response of the audience.

  • Passengers, Morten Tyldum · 2016
    n=14 (Lemgo, Cinema)

This science fiction with a fundamental optimistic belief in human expansion (technological and spacial) is an intimate theater on a space ship of sheer enormity. The lack of an alien threat helps to focus on the existential situation (mainly) two people are in. Therefore we can exploit how the audience involves with the development of the couple and how the the imminence both have to deal with affects visually and especially at the sound design.

  • American Psycho, Mary Harron · 2000
    n=16 (Berlin, Lecture Hall)

Summer 2016 · Research Sessions

We probably won’t be able to include the following movies, because of poor attendance and we had an essential change in questionnaire structure. We might be able to run additional sessions to increase the required number of test persons; the sessions are not necessarily bound to take place at the same location/at the same time. But, the lack of questionnaire quality does not recommend it.

Guardians of the Galaxy, James Gunn · 2014
n=8 (Lemgo)

Victoria, Sebastian Schipper · 2015
n=12 (Lemgo)

A Fish called Wanda, Charles Crichton/John Cleese · 1988
n=8 (Lemgo)

Fight Club, David Fincher · 1999
n=7 (Lemgo)

Martyrs, Pascal Laugier · 2008
n=7 (Lemgo)

Passengers Visit 1 and 2


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.


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 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.