Syllabus- Collab Spring 2014- PSAM 5550

AMT, Parsons, The New School for Design, MFA Design and Technology



The Digital Self: Interfacing The Body

Collaboration with OpenBCI


Course Dates: Jan 30, 2014 – May 15, 2014

Meeting Times:  Thursdays 7:00 pm – 9:40 pm

Location: 6 East 16th Street 1204A



Aisen Caro Chacin

Post-Graduate Fellow, Full-Time Faculty | Parsons The New School for Design


Conor Russomanno

Adjunct Faculty | Parsons The New School for Design

Co-Founder | OpenBCI


Supporting Faculty & Technical Mentor:

Joel Murphy

Hardware Lead | OpenBCI

Physical Computing Professor | Parsons, The New School


Course Description:

“We see with our brain, not with our eyes.” -Paul Bach-Y-Rita

As computing devices become more integrated with our physiology, designers and engineers are shifting their scope to biometric in/output interfaces. In this course students will explore the electric network of the human body, and develop an in-depth understanding of the its biological signals by experimenting with a variety of biometric sensors. This course is offered in collaboration with OpenBCI, a cutting-edge, open-source human-computer interface platform. OpenBCI facilitates novel methods of retrieving and interpreting biological signals emitted from the human body. This hardware is capable of tracking ECG (heart rate), EMG (muscle activity), and EEG (brain activity), and interfaces easily with electronic prototyping platforms such as Arduino. Learning more about anatomy and the contact potential with these devices will instigate students to design new and experimental interfaces for computing media. By working together students will build and share creative applications of the technology and become developers of the open-source community that powers OpenBCI.

This class will  engage students in understanding the body’s electric potential, and spark new ideas of human computer interaction. Our goal is to create experimental software and hardware applications that are in sync with our anatomy, e.g. directing a person’s path with galvanic vestibular stimulation, controlling robotics or virtual interfaces via neurofeedback, mapping and re-visualizing heart rate, or composing music with your muscle activity. Students will measure resistance, capacitance, and learn how to use the body as an electronic component in circuit design. Classes will range from galvanic electricity labs to neurofeedback coding sessions, and will engage students in understanding the body’s electric potential, sparking new relationships between humans and computers. Students will explore conceptual models which will critique, enhance, and innovate in the field of Human Computer Interaction and become citizen neuroscientists of the OpenBCI community.

About Our Collaborators:

What is OpenBCI?

OpenBCI is a versatile and affordable 8-channel signal capture platform built around Texas Instrument’s ADS1299 Analog Front End IC. We designed it to give the world access to high-quality, raw EEG/EMG/ECG data with minimal power consumption. OpenBCI is compatible with any type of electrode (active or passive) and can interface nearly all modern electronics prototyping platforms such as Arduino. OpenBCI is supported by an ever-growing, open-source software framework of signal processing and data analysis algorithms.

What Makes OpenBCI Different?

Today, the leading human-computer interface companies distribute fixed devices with limited or closed access to the algorithms that translate raw body signals to meaningful data. These devices are powerful and effective for application development but not ideal for R&D requiring adjustable hardware setups and direct control over the signal processing techniques. OpenBCI is fully accessible and powered by an open-source community of hardware and software builders, making it easy for creators of any skill level and ideal for researchers who haven’t yet settled on the perfect system design. The OpenBCI platform is intended to serve as a malleable starting point in the rapidly growing field of human-computer interfacing. Our motto: “What can we build together?”

“As the most important phenomenon in the universe, intelligence is capable of transcending natural limitations, and of transforming the world in it’s own image. In human hands, our intelligence has enabled us to overcome the restrictions of our biological heritage and to change ourselves in the process. We are the only species that does this.” – Ray Kurzweil

Learning Objectives:

  • Knowledge about the rapidly emerging fields of bio-sensing and human-computer interfacing.

  • Experience engaging with the open-source (hardware & software) worlds to foster community-driven research and development.

  • Experience working with an early-stage startup that promotes openness by having a business model that harnesses the energy of the open-source movement.

  • Experience collaborating with people of various disciplines to execute a common goal.

  • Acquire circuitry, hardware, and interface design prototyping skills.

  • Demonstrate critical thinking skills in search for the usability and potential applications of the technologies introduced in the course labs.

  • Advance independent research and conceptual models to be executed as functional prototypes.

  • Learn to propel their designs beyond the classroom, and prepare material for HCI, ACM, and other design conferences.

  • Have an in depth understanding about the human body’s electric potential, able to identify how current technologies utilizing these methods work.

  • Learn the language and important precedents in the field of Human Computer Interaction.


Class Topics:

Human Voltage, Neurofeedback, Electroreception, Galvanic Potential, Body Capacitance/Resistance, Electrogenesis, Human Computer Interaction, Augmented Prostheses, Sensory Displays, Open Hardware, Biometrics, Gestural Interfaces, Physiology.


Class Lessons:

– thorough understanding of electricity flow

– how/where/why/when does the body produce electricity

– circuit design & various body sensors

– basic understanding of EMG, ECG (or EKG), and EEG

– knowledge of all of the components of a fully-functioning brain-computer interface

– Data Flow: talking in 0s and 1s (SPI), serial, Bluetooth (& its limitation)

– Signal Processing: Raw EEG, FFT, classifiers, conceptual machine learning

– open-source hardware and software licenses: how to choose the best one for your project

– Version Control & Github: how to pull, commit, push, branch, fork, create your own repository, so you can work with other people in the open-source community

– the basics about embarking on your own crowd-funded startup (Kickstarter, social media, collaboration, community involvement) – get a Kickstarter employee to come talk…



Note: In the nature of OpenBCI’s mission, we are encouraging open source projects, but students are not required to keep their work open source. Students own all intellectual property with regards to the work that they produce in this course.

Project I Guidelines:

Students will work in groups to create a project that implements any number and/or type of biometric sensors. The project is very open in nature but must integrate a unique PCB design.


Project II Guidelines:

Students will work in groups to create projects with or for the OpenBCI platform (or similar HCI platform). Areas of focus could include:

1) Implementations of the technology (opportunity to present work at RE/Mixed Media Festival)

2) Conceptual or polished public-facing content to improve the functionality or public image of the OpenBCI brand

3) Website interface/functionality additions, enabling better collaboration and engagement for the OpenBCI community

4) “How-to” or “getting started” guides for newcomers to the OpenBCI platform.


Course Calendar:

Class 1 (1/30/14)

Introductions:What interests you most about this class?

Review Syllabus

Talk about OpenBCI

Assignment: Inspiration Research (a project that exemplifies your interest in taking this class)

Prepare for a “Show & Tell.” Bring a project to class that is relevant to this course and be prepared to demo it to your peers.


Class 2 (2/6/14) – Note: Last day to add class (2/7/14)

Technology Demo: Pulse Sensor / MindFlex / NeuroSky / Theremin / Galvanic Skin Response / Temperature Sensor / Bone Conduction / Biometrics

Presentations: Share the ideas that inspire you in a 3 min presentation. This will allow your classmates to learn more about your interests and find compatible collaborators.

Select team members for collaborative project one.

Assignment: Finalize groups for Project I and begin conceptual brainstorming.


Class 3 (2/13/14) – Note: Last day to drop class (2/13/14)

Lecture: The Spark of Life

Lab: Brainstorming for Bodystorming

Assignment: Select an idea and make 3 mini prototypes, one of these must include breadboarding.

Class 4 (2/20/14)

Introduction to Neuroscience Lecture: Neuroscientist Guest Lecturer Zarinah Agnew

Lab: PCB Design Part I (Intro to Circuit Design)

Breadboarding, schematics, and laying out traces in Fritzing/EagleCAD.

Assignment: Work on PCB design.


Class 5 (2/27/14)

Lecture: Senses and Sensors: Transducers of the Physical World

Lab: PCB Design Part II (Maximizing space, custom board outlines, and checking designs)

Assignment: Finish PCB design

Class 6 (3/6/14)

Lecture: Generating Biopower

What methods can we use to capture electrical power from our bodies? How can we convert mechanical, thermal, chemical  to electrical energy?

Lab: PCB Design Part III (Introduction to PCB printing, exporting files)


Class 7 (3/13/14)

Lab: PCB Design Part IV (PCB printing with CNC router or InkJet flexible circuits)

Work Session: In-class time to work on Project I

 Assignment: Finish Project I


Class 8 (3/20/14)

Presentations – Project I



3/27/14 – [Spring Break] – No Class



Class 9 (4/3/14)

Lecture: Interfacing The Brain (techniques, examples, and considerations for the future)

Lab: Get up and running with OpenBCI. Every student will download the OpenBCI code from Github, get the code running on Arduino & Processing, and have a chance to see their brainwaves in real-time using research-grade electrode caps.

Introduce Project II

Assignment: Start OpenBCI Assignment #1 (start of 2-week assignment): Creatively map the biometric data output of OpenBCI onto a visualization (physical or virtual).


Class 10 (4/10/14)

Lecture: Communicating With OpenBCI (applicable to most biometric sensors)

  • Talking to OpenBCI: ADS1299, serial peripheral interface (SPI), 0s and 1s, building an Arduino Library

  • Listening to brain waves and other electrical signals: raw EEG, filters, data rates, bluetooth

  • Making sense of biometric data: signal processing, FFT, introduction to classifiers and machine learning

Assignment: Finish OpenBCI Assignment #1 (end of 2-week assignment): Creatively map the biometric data output of OpenBCI onto a visualization (physical or virtual).


Class 11 (4/17/14)

Lecture: Understanding Open Source

  • Using version control for open source code (via Github)

  • Overview of open source licences (for hardware and software)

  • Community-building (maximizing social media, coordinating hackathons/meetups, )

  • Funding opportunities (Kickstarter and other crowd-funding, grants, pricing your creations)


Assignment: Students have the option of presenting Project I or In-progress Project II at RE/Mixed Media Festival ( If you do not present, you must still attend the event.


Class 12 (4/24/14)

Workshop: experimenting with OpenBCI and other biometric sensors

Assignment: Work on Project II


Class 13 (5/1/14)

Workshop: experimenting with OpenBCI and other biometric sensors

Assignment: Work on Project II


Class 14 (5/8/14)

Work Session: in-class time to work on Project II

Assignment: Finish Project I & prepare final presentation


Class 15 (5/15/14) – Last Day Of Class

Final Presentations: Present Project II



University Resources:

The university provides many resources to help students achieve academic and artistic excellence. These resources include:

In keeping with the university’s policy of providing equal access for students with disabilities, any student with a disability who needs academic accommodations is welcome to meet with me privately. All conversations will be kept confidential. Students requesting any accommodations will also need to contact Student Disability Service (SDS). SDS will conduct an intake and, if appropriate, the Director will provide an academic accommodation notification letter for you to bring to me. At that point, I will review the letter with you and discuss these accommodations in relation to this course.


University, Divisional/School, and Program Policies:


Academic Honesty and Integrity

Compromising your academic integrity may lead to serious consequences, including (but not limited to) one or more of the following: failure of the assignment, failure of the course, academic warning, disciplinary probation, suspension from the university, or dismissal from the university.


University Policy

The New School views “academic honesty and integrity” as the duty of every member of an academic community to claim authorship for his or her own work and only for that work, and to recognize the contributions of others accurately and completely. This obligation is fundamental to the integrity of intellectual debate, and creative and academic pursuits. Academic honesty and integrity includes accurate use of quotations, as well as appropriate and explicit citation of sources in instances of paraphrasing and describing ideas, or reporting on research findings or any aspect of the work of others (including that of faculty members and other students). Academic dishonesty results from infractions of this “accurate use”. The standards of academic

honesty and integrity, and citation of sources, apply to all forms of academic work, including submissions of drafts of final papers or projects. All members of the University community are expected to conduct themselves in accord with the standards of academic honesty and integrity.


Students are responsible for understanding the University’s policy on academic honesty and integrity and must make use of proper citations of sources for writing papers, creating, presenting, and performing their work, taking examinations, and doing research. It is the responsibility of students to learn the procedures specific to their discipline for correctly and appropriately differentiating their own work from that of others. Individual divisions/programs may require their students to sign an Academic Integrity Statement declaring that they understand and agree to comply with this policy.


The New School recognizes that the different nature of work across the schools of the University may require different procedures for citing sources and referring to the work of others. Particular academic procedures, however, are based in universal principles valid in all schools of The New School and institutions of higher education in general. This policy is not intended to interfere with the exercise of academic freedom and artistic expression.


Academic dishonesty includes, but is not limited to:

  • Cheating on examinations, either by copying another student’s work or by utilizing unauthorized materials.

  • Using work of others as one’s own original work and submitting such work to the university or to scholarly journals, magazines, or similar publications.

  • Submission of another students’ work obtained by theft or purchase as one’s own original work.

  • Submission of work downloaded from paid or unpaid sources on the internet as one’s own original work, or including the information in a submitted work without proper citation.

  • Submitting the same work for more than one course without the knowledge and explicit approval of all of the faculty members involved.

  • Destruction or defacement of the work of others.

  • Aiding or abetting any act of academic dishonesty.

  • Any attempt to gain academic advantage by presenting misleading information, making deceptive statements or falsifying documents, including documents related to internships.

  • Engaging in other forms of academic misconduct that violate principles of integrity.

(This is an abridged version of the policy. For the full policy text, which includes adjudication procedures, visit: )


Guidelines for Studio Assignments

Work from other visual sources may be imitated or incorporated into studio work if the fact of imitation or incorporation and the identity of the original source are properly acknowledged. There must be no intent to deceive; the work must make clear that it emulates or comments on the source as a source. Referencing a style or concept in otherwise original work does not constitute plagiarism. The originality of studio work that presents itself as “in the manner of” or as playing with “variations on” a particular source should be evaluated by the individual faculty member in the context of a critique.

Incorporating ready-made materials into studio work as in a collage, synthesized photograph or paste-up is not plagiarism in the educational context. In the commercial world, however, such appropriation is prohibited by copyright laws and may result in legal consequences.


Open Source Policy

You are encouraged to work in groups, but unless otherwise specified  you must turn in your own work. Copying/pasting and reusing code is a key part of the programming process,

especially while learning. You often learn best by modifying working examples rather than

starting from scratch. We stand on the shoulders of giants;  that’s the essence of the opensource philosophy. However, there is a very important caveat: any code you borrow and/or modify must be labeled as such. That is, you must include, in your work, the name of the author, the source URL, and you must make clear which lines of code are not yours. If you fail to do this, you will fail the class. It is very, very easy to get this right, though, so if you take a moment’s time to label your work correctly, you will not have a problem. Just be diligent and honest.


Course Policies:



Students are responsible for all assignments, even if they are absent. Late papers, failure to complete the readings assigned for class discussion, and lack of preparedness for in-class discussions and presentations will jeopardize your successful completion of this course.



Class participation is an essential part of class and includes: keeping up with reading, contributing meaningfully to class discussions, active participation in group work, and coming to class regularly, prepared and on time.



In rare instances, I may be delayed arriving to class. If I have not arrived by the time class is scheduled to start, you must wait a minimum of thirty minutes for my arrival. In the event that I will miss class entirely, a sign will be posted at the classroom indicating your assignment for the next class meeting.


Additional Course Information:


Student Course Ratings

During the last two weeks of the semester, students are asked to provide feedback for each of their courses through an online survey and cannot view grades until providing feedback or officially declining to do so. Instructors rely on course rating surveys for feedback on the course and teaching methods, so they can understand what aspects of the class are most successful in teaching students, and what aspects might be improved or changed in future. Without this information, it can be difficult for an instructor to reflect upon and improve teaching methods and course design. In addition, program/department chairs and other administrators review course surveys.


Attendance & Grading Policy:


Parsons’ attendance policy was developed to encourage students’ success in all aspects of their academic programs.  Parsons promotes high levels of attendance because full  participation is essential to the successful completion of coursework, and enhances the quality of the educational experience for all, particularly in courses where group work is integral.  Students, therefore, are expected to attend classes regularly and promptly and in compliance with the standards stated in course syllabi. Faculty members may fail any student who is absent for a significant portion of class time.  A significant portion of class time is defined as three absences for classes that meet once per week and four absences for classes that meet two or more times per week.  During intensive summer sessions a significant portion of class time is defined as two absences.  Lateness or early departure from class may also translate into one full absence. Faculty will make attendance standards clear, in writing, at the beginning of the semester.  Students may be asked to withdraw from a course if their habitual absenteeism or tardiness has a negative impact on the class environment. Students who must miss a class session should notify his or her instructor and arrange to make up any missed work as soon as possible.  Students who anticipate a potentially lengthy absence must immediately inform the program Chair or Director and must explain the extenuating circumstances in writing.  Students must receive advance approval for the absence in order to ensure successful completion of the course.  A Leave of Absence or Withdrawal from Program will be recommended if the absence would compromise the student’s ability to meet course requirements and standards.



Classes meeting 2 time per week: 4 absences are grounds for failure.



Two (2) tardies will be counted as one absence.

5 minutes is considered tardy.

The following may be counted as tardy:

· Coming to class without the required materials

· Sleeping in class

· Being asked to leave class because of disruptive behavior.

· Doing other course work in class.


Academic Warning

Students who do not complete and submit assignments on time and to a satisfactory standard will fail this class. It is a student’s responsibility to obtain missed assignment sheets from other classmates and make-up the work in time for the next class.

Course Expectations

In order to receive a grade for this course, students must actively participate in classroom discussions and critiques, and complete all the assigned projects, including mid-term & final projects.


Mid-semester Evaluations:

Mid-semester evaluations are issued to help students improve performance and make

progress. Although a grade may not be given, the comments will indicate your standing on a below – average – above scale.


Grade Descriptions (from SDS Guidelines):

A 4.0  Work of exceptional quality. 95-100%

These are projects that go above and beyond the expectations and requirements described in the assignment. They demonstrate substantial effort and achievement in the areas of critical thinking, technique and presentation.


A- 3.7  Work of very high quality.  90-94%


B+ 3.3  Work of high quality, higher than average abilities. 86-89%


B 3.0  Very good work that satisfies goals of course. 83-85%


The “B” student offers a clear and convincing structure to a visual endeavor that is more complex and unique than a project at the average level. The creator’s point of view and point of the project are merged successfully and organized fairly consistently throughout the project. Although minor structural problems may be present in the assignment, they do not hinder the overall outcome.


B-  2.7   Good work. 80-82%


C+ 2.3  Above Average work, Average understanding of course material. 76-79%


C 2.0  Average  work;  passable. 73 -75%


The student demonstrates an engagement with the assignment. The project will show that the creator can identify and work with key ideas and examples found in reference material. Typical of a “C” project is that the original problem or assignment once approached, does not develop further. Projects may also have organizational, technical weaknesses.


C- 1.7 Passing work but below good academic standing.  70-72%


D 1.0  Below average work; does not fully understand the concepts of the course. 60-70%


Although this is passable work, the project only answers the minimum requirements of the assignment. The projects shows very little effort, is incomplete, late or incorrect in its approach. The outcome shows a lack of full understanding and commitment on the part of the creator.


F 0  Failure, no credit. 0-59%


WF  Withdrawal Failing.


Instructors may assign this grade to indicate that a student has unofficially withdrawn or stopped attending classes. It may also be issued when a student fails to submit a final project or to take an examination without prior notification or approval from the instructor.  The WF grade is equivalent to an F in calculating the grade point average (zero grade points) and no credit is awarded.