Wait!

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Project title: Wait!

Project Description: 

This project targets on facilitating walking activity for users with vision impairment by incorporating TENS (transcutaneous electrical nerve stimulation) device as a form of haptics. People with blindsight—the ability to detect things in the environment without being aware of seeing them, are faced with the obstacles of perform daily activities without bumping into erect objects or surfaces. They need to use a stick to track obstacles or require guidance by another person when walking around buildings.

Wait! is a piece of wearable that addressed the demand of users with vision issues by providing audio and haptic feedback to alert users from being too close to impediments. It consisted of an ultrasonic sensor to detect real-time distance from the user to the object/surface in front of. When user has walked up too close towards the object/surface, the ultrasonic sensor will trigger the switch in the relay, generating the sound of a click and send low-voltage electrical pulses via TENS device to human body. Only when user stepped back, the electrical pulses will be put on halt. Henceforth, user are better supported and assisted in navigating indoor or outdoor spaces.

By incorporating an established TENS device, users are able to adjust the strength and frequency of pulse signals according to their own preference and level of comfortableness. The value could be set beforehand and saved for future uses with customization.

Project Context:  

EMS(Electrical Muscle Stimulation) and TENS has been widely employed in the field of medicine. They can be considered as supplements to conventional muscle training, particularly for therapeutic treatment and physical rehabilitation. TENS is more specifically used in pain treatment that it stimulates the nerves exclusively by delivering electrical signals that do not trigger muscle movement. Applying TENS signals to painful spots at the body can reduce discomfort and relieve pain (Gibson et al., 2019). 

Despite an emphasis on the field of medicine, there are emerging studies of using EMS as a form of haptics in the creative industry. Studies have been conducted around the cross-section of wearable devices, mixed reality, human-computer interaction and experience design. EMS has been used as a haptic input and output technology in wearable and textile-based computing through crafting comfortable textile electrodes (Pfeiffer & Rohs, 2017). EMS has also been incorporated into haptic interfaces to simulate the force feedback effect caused by a collision, in generating a mixed reality tennis game (Farbiz et al., 2007). With all the applications of EMS in non-traditional settings, TENS however, is yet to discovered and applied in other disciplines from an innovative perspective.

One case study that informed this project is Using Electrical Muscle Stimulation Haptics for VR. While traditional approaches in VR focus on lightweight objects via skin receptors such as vibro-tactile gloves, simulating heavy objects is still confronted with limitations by traditional methods of physical props or hand tethering (Burdea, 2000). This study explores how to better render heavy objects in VR via EMS in the form of wearables. Its main concept is to prevent the user’s hands from penetrating virtual objects by means of EMS. Tension is created in the user’s bicep, tricep, pectoralis, and shoulder muscles. The system stimulates up to four muscle groups to generate the desired tension, thereby constructing the desired realistic experience of touching the wall or lifting up heavy objects. 

The system is encapsulated into a small backpack, which could be worn by the user. The backpack contains a medical compliant 8-channel muscle stimulator, which is controlled from within the VR simulators via USB. Other components include a typical VR system consisting of a head-worn display (Samsung/Oculus GearVR) and a motion capture system (eight OptiTrack 17W cameras). 

This project informs the design of Wait! in the way that in a VR environment, users are less capable of sensing the surrounding while moving around – similar to be under the vision-impaired circumstance. Using EMS to generate muscle tension and henceforth simulate the weight of object is intriguing and very informative in terms of possible applications of muscle stimulation.

Other related works include vibration-based tactile haptics such as CyberTouch by Virtual Technologies (Burdea, 2000), pneumatic gloves using air pockets (Tarvainen & Yu, 2015), tethers and exoskeletons for fingers or upper body muscles. Passive haptics are also oftentimes used in VR to simulate the existence of objects such as still props and props placed by human or robot. Even though tactile haptic could potentially support a better texture rendering, it does not deliver a directional force that acts upon the user’s hands or muscle groups. Pneumatic gloves are also confronted with the similar challenge of representing heavyweight objects. Hence the utilization of EMS/TENS to activate muscles is of great value and importance to be further investigated.

Another study that I have looked into is Remote Controlled Human project which uses Spark Core, a TENS unit, and a relay to remotely control a human minion over WiFi. The Spark Core connects the TENS unit and user it attached to with the Internet of Things. With the TENS unit stimulating involuntary muscle movements, the relay acts as a bridge between the signal provider and the receiver. This project is a great reference for circuit construction, specifically how to bridge a commercialized healthcare product with computer softwares via a simple relay. It also extends the future possibility for hooking up sensors and writing one’s own sketches via the Spark IDE to generate outputs based on all kinds of conditions, such as rhythmic music input, light levels and et cetera.

Parts List:

  • 1 Arduino UNO
  • 1 TENS unit (TENS 3000)
  • 1 Ultrasonic Sensor HC-SR04
  • 1 relay unit
  • 1 Felt hat
  • Breakout cables
  • 3 Male-to-Male jumper cables
  • 2 Male headers
  • Wire cutters/strippers
  • Sewing kit
  • Small slotted screwdriver

Circuit Diagram:

circuit-diagram

Github Code | Link to Video

Wearability Assessment/Priorities:

  1. Unobtrusive placement. (The hat works at the appropriate area of human body without impeding dynamic body movements.)
  2. Design for human perception of size. (This wearable is designed to minimize thickness and weight as much as possible. The sensor is within the range of normal hat weight to be unobtrusive and transparent.)
  3. Containment. (This piece of wearable contains materials of all electronic components, wires, electrodes, etc. While some of these things are malleable in form, there are many with fixed volume that one needs to consider how the ‘insides’ bring to the outer form.)

Final Photos:

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Challenges & Successes:

Figuring out a way to incorporate TENS signal that is non-harmful yet effective on human bodies was one of the biggest challenges during the early stage of this project. As electrical muscle stimulation has a safe range of usage and a varied level of comfortableness upon users across different demographics, utilizing TENS needs thorough preliminary preparation and physiological backup. Out of the safety concern, I decided to proceed with a relatively safe and minimal side effect TENS device which has been clinically tested and commercially employed. 

Reference to Remote Controlled Human project, I was able to hack into TENS 3000 unit and control its digital switch using a relay and Arduino UNO. The analog control of TENS unit would be much more complicated with an established device. 

The construction of this project was also one big challenge in terms of fitting the whole circuit into the interior of a hat while maintaining enough space for user’s head to fit in. I mapped the circuit onto the inner surface and tried to design an optimal route for wires to connect to each component without taking extra space. The Ultrasonic sensor was placed in front of the hat with the other part of sensor hidden in the hat brim by poking out two holes. The wires were attached underneath with another cut to hide the connection. However, it still leaves visible wires connected to battery or electrodes that users might find complicated and troublesome when attaching TENS pads onto the body.

Next Steps:

Furthering this project, I would like to experiment with controlling TENS/EMS signals in an analog way rather than digital. The wearable could be elevated if it can sense body signal as inputs and adjust the output automatically with the assist of Arduino programming. However, figuring the way of connection and making sure the safety range of pulse stimulation are going to be the two biggest challenges.

In order to achieve that, it might require the abandonment of established TENS units but to figure out a way to manually set frequency/strength of electrical stimulations. It adds to the level of insecurity and danger as it is not monitored under a controlled environment.

Incorporating EMS into other creative disciplines as an innovative medium would be interesting to be explored, such as with the cross-section in music, performance art, writing, education and et cetera.

Bibliography:

Farbiz, F., Yu, Z., Manders, C., & Ahmad, W. (2007). An electrical muscle stimulation haptic feedback for mixed reality tennis game. SIGGRAPH ’07.

Follmer, S., Leithinger, D., Olwal, A., Cheng, N., & Ishii, H. (2012). Jamming user interfaces. Proceedings Of The 25Th Annual ACM Symposium On User Interface Software And Technology – UIST ’12. doi: 10.1145/2380116.2380181

Gibson, W., Wand, B., Meads, C., Catley, M., & O’Connell, N. (2019). Transcutaneous electrical nerve stimulation (TENS) for chronic pain – an overview of Cochrane Reviews. Cochrane Database Of Systematic Reviews. doi: 10.1002/14651858.cd011890.pub3

Janczyk, M., Skirde, S., Weigelt, M., and Kunde, W. (2009). Visual and tactile action effects determine bimanual coordination performance. Hum. Mov. Sci. 28, 437–449. doi: 10.1016/j.humov.2009.02.006

Jones, S., Man, W., Gao, W., Higginson, I., Wilcock, A., & Maddocks, M. (2016). Neuromuscular electrical stimulation for muscle weakness in adults with advanced disease. Cochrane Database Of Systematic Reviews, 2016(10). doi: 10.1002/14651858.cd009419.pub3 

Lee, J., Kim, Y., & Jung, H. (2020). Electrically Elicited Force Response Characteristics of Forearm Extensor Muscles for Electrical Muscle Stimulation-Based Haptic Rendering. Sensors (Basel, Switzerland), 20(19), 5669. https://doi.org/10.3390/s20195669

Lopes, P., You, S., Cheng, L.-P., Marwecki, S. & Baudisch, P. (2017). Providing Haptics to Walls & Heavy Objects in Virtual Reality by Means of Electrical Muscle Stimulation.. In G. Mark, S. R. Fussell, C. Lampe, m. c. schraefel, J. P. Hourcade, C. Appert & D. Wigdor (eds.), CHI (p./pp. 1471-1482), : ACM. ISBN: 978-1-4503-4655-9

Pavani, F., Spence, C., and Driver, J. (1999). Visual capture of touch (tactile ventriloquism); out-of-the-body experiences with rubber gloves. J. Cogn. Neurosci. 11:14.

Pfeiffer, M., Schneegass, S., & Alt, F. (2013). Supporting interaction in public space with electrical muscle stimulation. Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication.

Robertson, A. (2021). Meta’s sci-fi haptic glove prototype lets you feel VR objects using air pockets. Retrieved 21 April 2022, from https://www.theverge.com/2021/11/16/22782860/meta-facebook-reality-labs-soft-robotics-haptic-glove-prototype

Spotlight Presentation – Chronic Pain Management Case Study

Wearable Technology for Chronic Pain Management

Case study: Quell

BACKGROUND

Chronic pain is commonly defined as pain with a duration over six months (Turk & Okifuji, 2001). Chronic pain caused by diseases and injuries can dramatically reduce life quality as it is linked to the increase in depression, anxiety, sleep disturbance, productivity loss, and poor decision-making performances (Apkarian et al., 2003).

Current treatment for chronic pain sufferers include prescribed nonprescription analgesics, physical therapy, or interventional procedures to ameliorate pain. Transcutaneous electro-nerve stimulation (TENS), surgery, and implanted neural stimulators are also sometimes recommended by medical specialists. However, these current treatments are oftentimes not up to expected efficacy and safety. Take opioids as an example: despite being effective for acute pain treatment, opioids show poor efficacy for chronic pain with potential side-effects of abuse, dependence, misuse, and accidental overdose (Volkow & McLellan, 2010).

The objective of this case study of Quell is to evaluate one of the most commercially competitive TENS products as Quell combines neurostimulation and digital health technologies to relieve chronic pain. Analyzing and evaluating this product provides a better insight into health technology and the inner mechanism of such product design. 

CASE EVALUATION

Product Overview

Quell has been developed by NeuroMetrix, which is a company focused on the development and commercialization of non-invasive medical devices specializing in diagnosing and treating pain and neurological disorders. NeuroMetrix mainly focuses on three products DPNCheck®, ADVANCE® and Quell®, with the previous two products being diagnostic devices featuring on detection and evaluation. 

Quell is a wearable neurostimulation device designed for lower extremity chronic pain treatment through relieving knee, foot and leg pain. It consisted of four main components: a therapy pod, an electrode array, a band and a mobile app. Compatible with smartphones and Apple Watch,  users can place a Quell device on the upper calf and continue their daily activity with automated prescription strength pain relief. Users are able to source information on therapy sessions, customize therapy and monitor past activities and sleep statistics. The app also suggests alternative doses according to weather conditions.

Working Mechanism

To better understand how this device works, one needs to acknowledge two terminologies. The first one is Transcutaneous electrical nerve stimulation (TENS), which stimulates sensory nerves in people’s legs with safe, painless, and precise electrical impulses to trigger natural pain relief response. The second is the Gate Control Theory of Pain, published in 1965. It proposes a mechanism in the dorsal horns of the spinal cord which acts like a gate that either inhibits or facilitates transmission from the body to the brain based on the diameters of the active peripheral fibers and the dynamic action of brain processes (Melzack & Wall, 1965). Quell incorporates TENS to stimulate sensory nerves in users’ legs with safe, painless, and precise electrical impulses to trigger a natural pain relief response. 

Target Audience

As a digital health technology, Quell has a specific target user profile which is people experiencing chronic knee pain. Considering most people with chronic pain complain of disturbed sleep and daytime lethargy, as polysomnography studies show chronic pain patients have shorter sleep duration, lower sleep efficiency and greater number of periodic leg movements, Quell strives to address both pain management and sleep issues for chronic pain sufferers.

Chronic knee pain is one of the most common forms of chronic pain. Current treatment for chronic pain sufferers include prescribed nonprescription analgesics, physical therapy, or interventional procedures to ameliorate pain. TENS, surgery, and implanted neural stimulators are also sometimes recommended by medical specialists. Osteoarthritic knee pain may be worse at night leading to sleep abnormalities and TENS would be an effective, non-invasive, low-risk treatment for chronic pain treatment. 

Shortcomings and Limitations

One of the biggest shortcomings with wearable technology in the consumer market in general is security concerns. Nowadays, security and privacy issues of wearable devices have been gradually more prominent, mostly about user data being manipulated, insecure communication, data loss, and lack of encryption. Especially in the health industry, how to safeguard patients’ personal data and privacy is still yet to be investigated.  

Besides the issue of privacy, Quell has several limitations on the basis of its hardwares and product design. First of all is the lifespan of Quell electrodes. As the gel pads on the electrodes are primarily water, users may observe signs of wear during the course of normal use. From the user manual, it is recommended that electrodes are replaced at 2 week intervals to maximize therapy efficacy and experience. Secondly, Quell was designed to be placed at a fixed location, the upper calf in one leg. For users with chronic pain on two legs or other parts of the body. The efficacy of Quell might be compromised accordingly. Last but not least, there have been critics over Quell on its effectiveness as a simple “placebo” effect. As not much academic studies have been carried out over this product, the comprehensive evaluation of Quell still needs further research and investigation.

RELEVANCE TO OUR COURSE

Even though Quell is a commercialized wearable product, its working mechanism still follows the fundamental schema of detection and sensing, data collection and analysis, and feedback realized with actuators. Referencing this product could bring us great insights about how to approach design problems and solutions with an industrial perspective. 

Researching into this product allows us to think about the user experience part of wearable technology and how we can approach real-world problems with digital tools. Different from our past projects which focus more on personal expression and understanding, a commercialized product is curated out of the needs of potential users in trying to deliver a comfortable and efficient experience for them. Commercialized products emphasize stability and efficacy as higher priorities, that we could benefit such perspectives from their iteration and evaluation processes.

RELATED PRODUCTS

There are a number of similar products on the consumer market which utilizes TENS to address daily pain management. Ireliev is one of the widely accepted digital health technologies which incorporates not only TENS, but also EMS systems. EMS stands for “Electrical Muscle Stimulation” and is the elicitation of muscle contraction using electrical impulses. EMS helps activate the muscles to increase strength and endurance, and to facilitate quicker recovery. Ireliev consisted of more components comparing to Quell, with a Wireless TENS + EMS Muscle Stimulator Hand Control, 2 Wireless TENS + EMS Pods, 2 3″ x 5″ Electrode Pads, and 4 Pod Decals (2-CH2, CH3 and CH4).

Another product that features great capabilities is PowerDot 2.0 Duo. With a minimalistic yet powerful visual appearance, PowerDot’s platform combines the effectiveness of TENS to relieve pain with benefits of NeuroMuscular Stimulation (MES) to improve circulation for recovery, reduce atrophy during injuries, and improve the wellness of joints. 

Using TENS is generally safe with no obvious side effects. However, adhesive pads can sometimes cause allergic reactions for users. TENS can also cause metallic or electronic implants, such as defibrillators and cardiac pacemakers into the state of malfunction. Users who are experiencing such products should prevent TENS units from the eyes, mouth, head, neck, and other sensitive areas.

CONCLUSION

As the cost of hardware decreases and technology becomes more inexpensive, wearable technologies are progressively intertwined into people’s lives. TENS power unit demonstrates how we could use the mechanism of biological signals from our body and feedback such outputs to alter our body status. Wearable technology not merely serves as a device of data collection but has much more potential as a tool of active intervention. The remedial effect of wearable technology is also worthy further investigation. How to create digital wearables on the basis of principles of calm technology: being non-intrusive yet instructive to target audiences requires additional efforts to be put into. 

BIBLIOGRAPHY

Apkarian AV, Sosa Y, Krauss BR, et al. “Chronic pain patients are impaired on an emotional decision-making task”. Pain. 2004;108:129-136. doi:10.1016/j. Pain.2003.12.015.

Dunn KM, Saunders KW, Rutter CM, et al. “Opioid prescriptions for chronic pain and overdose: A cohort study”. Ann Intern Med. 2010. doi:10.7326/00034819-152-2-201001190-00006.

Gozani, Shai N, and Xuan Kong. “Real-World Evidence For The Widespread Effects Of Fixed-Site High- Frequency Transcutaneous Electrical Nerve Stimulation In Chronic Pain”. Journal Of Pain &Amp; Relief, vol 07, no. 04, 2018. OMICS Publishing Group, https://doi.org/10.4172/2167-0846.1000329.

Gozani, Shai et al. “1009 Predictors Of Improved Pain Interference With Sleep In A Real-World Chronic Pain Cohort By Transcutaneous Electrical Nerve Stimulation”. Sleep, vol 42, no. Supplement_1, 2019, pp. A406-A406. Oxford University Press (OUP), https://doi.org/10.1093/sleep/zsz067.1006.

Melzack, Ronald, and Patrick D. Wall. “Pain Mechanisms: A New Theory”. Pain Forum, vol 5, no. 1, 1996, pp. 3-11. Elsevier BV, https://doi.org/10.1016/s1082-3174(96)80062-6.

“Neurometrix”. Neurometrix.Com, 2022, https://www.neurometrix.com/.

“Theragun Powerdot 2.0 Muscle Stimulator | TENS, EMS | Therabody.Com – Therabody”. Therabody, 2022, https://www.therabody.com/ca/en-ca/powerdot-duo-red.html.

Turk DC, Okifuji A. “Pain terms and taxonomies”. In: Loeser D, Butler SH, Chapman JJ, D.C. T, eds. Bonica’s Management of Pain. 3rd ed. Lippincott Williams & Wilkins; 2001:17-25.

Volkow N, McLellan T. “Opioid Abuse in Chronic Pain — Misconceptions and Mitigation Strategies”. N Engl J Med. 2016;374(1253-1263). doi:10.1056/ NEJMra1507771.

“Wireless TENS + EMS Muscle Stimulator | Wearable System By Ireliev”. Ireliev, 2022, https://ireliev.com/product/therapeutic-wearable-system.

Musec

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illusatrations

Project title: Musec

Members: Aaditya VAZE, Ellie HUANG

Project Description: 

For this project, we are exploring alternative forms of control connecting to digital keyboards. Drawing from our own experience, we initially identified two main pain points during the interaction process: 1. users need to flip music notes which makes the act of play less smooth; 2. users need to press on one foot to initiate actions of the sustain pedal, which takes more time to be trained comparing to just utilizing the upper body.

In order to sense signals in the most efficient way, we incorporated Muse headband – a wearable brain sensing headband that measures brain activity via 4 eletroencephalography (EEG) sensors. For project Musec, we used EEG sensors for blink detection, as well as accelerometer to sense head position – tilting towards either left or right.

Users are able to control the pedal with actions of blinking (noding in another version) and flip pages left or right via the actions of head tilting. Musec strives to incorporate beginning learners, piano practitioners, and marginalized community of disabled people as target audiences that they could potentially benefit from the new ways of interaction.

Final Photos:

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Parts List:

  • Muse Band 2014
  • Relay module
  • 6.35mm jack
  • Arduino Uno
  • Digital Keyboard
  • Mobile phone & laptop

Circuit Diagram:

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Github Code

Project Context:

Working around the Muse headband has pushed us out of comfort zone of established knowledge to learn more about how brain signals are detected and processed. We have explored around projects incorporating EEG and EMG (electromyography) sensors to better our understanding about the brain-computer interface realm.

One of the examples that we looked at is Psylink an open source neural interface for non-invasive EMG. This project is named Prototype 8. There is a lack of EMG projects as we browse around the internet, despite being a powerful tool. Technical difficulties with tiny muscular electrical signals amongst other signal noise were often mentioned, which leads to a difficulty in interpretation. For Prototype 8, Dave Rowntree has trained gesture detection AI to categorize displayed gestured into controlling video game interfaces. The current prototype uses a main power board hosting an Arduino Nano 33 BLE Sense and a boost converter to pump up the AAA battery to provide 5 volts for the Arduino and a selection of connected EMG amplifier units. The EMG sensor is based around the INA128 instrumentation amplifiern. The EMG samples along with data from the IMU on the Nano 33 BLE Sense, are passed along to a connected PC via Bluetooth, running the PsyLink software stack.

Seeing other’s work was of tremendous help for our team to realize the transmission process from signal detection to actuator delivery. Other related works that we reference to include a Brain-Computer-Music-Interface . The BCMI allows users to create music using nothing more than eye movement and brainwaves. This project was developed by a team headed by Eduardo Miranda, a composer and computer music specialist from the UK’s University of Plymouth. The system is not yet wireless, but uses a laptop computer, related software, 3 electrodes and an EEG amplifier, which can be built for under a reasonable budget. There are four icons that are designed to be responsible for sounding pitch, rhythm, and controlling the strength & speed of notes. Using brainwaves users can nearly immediately produce a full range of musical notes from this device by simply looking intently at one of four icons. However, similar to learning to play a musical instrument, playing music with this device requires skill and learning. In this way it is interesting in designing its own language system of music communication and respective learning path.

Other projects that we have delved into include works that are already commercialized, such as Ctrl lab – a New York-based startup developing a wristband that translates neuromuscular signals into machine-interpretable commands, and later bought by Facebook in 2019; Tap strap – a hand worn wearable that allows users to type, mouse, and use air gestures to control any device with one hand.

These references have greatly oriented us into putting our project concept into realization. Differentiating between EEG/EMG signals furthered our understanding about stability of system and curation of a more ideal user experience.  As many people have worked with interactive music interfaces  with different sensors, we also would like to incorporate our own perspective into the play, especially with our own experiences interacting with current music interfaces – digital keyboard per se. The control and manipulation of sustain pedal and page flips is the biggest concern that we would like to address under the assist of signal sensors/accelerometer. Having the auto-detection speeds up the decision process that users are making while multitasking (playing keyboard yet thinking about the timing to either press on pedal or flip pages). In this way, the rendering of music piece requires less attention to be skewed away and smooths up the whole performing process.

Explanation of Design Choices:

  • Detection of nodes: Initially we started with using absolute value, but considering user experience we decided to avoid that. Limiting users to node only on a certain range of height is not ideal nor practical. We used previous state/current state comparison to calculate the difference of height in detecting the action of node. Right now no matter what initial position the user is at, the band will be calibrated into their head position.
  • Flipping left and right: We used tilting head into left / right to decided whether the page is flipped towards which direction. It matches with general assumptions of human behaviour. We decide to detect tilting head instead of turning head around, based on the fact that players need to keep their eye on the music notes, while turning head might hinder such focus.
  • Tempo/Rhythm – Metronome: It’s difficult for piano/keyboard beginners to know when to press on the sustain pedal. The actions of blinking or noding at the start of each section match with the rhythm and clicking sound generated by relay serves as a metronome.

References:

  • Dwivedi, A., Gerez, L., Hasan, W., Yang, C. and Liarokapis, M., 2019. A Soft Exoglove Equipped With a Wearable Muscle-Machine Interface Based on Forcemyography and Electromyography. IEEE Robotics and Automation Letters, 4(4), pp.3240-3246.
  • Pages.uoregon.edu. 2022. Electronic Music Interactive, 2nd edition. [online] Available at: <https://pages.uoregon.edu/emi/about.php>
  • Liu, M., 2022. An EEG Neurofeedback Interactive Model for Emotional Classification of Electronic Music Compositions Considering Multi-Brain Synergistic Brain-Computer Interfaces. Frontiers in Psychology, 12.
  • Miranda, E., Magee, W., Wilson, J., Eaton, J. and Palaniappan, R., 2011. Brain-Computer Music Interfacing (BCMI): From Basic Research to the Real World of Special Needs. Music and Medicine, 3(3), pp.134-140.
  • Mirazimzadeh S.A., McArthur V. 2020. Automatic Page-Turner for Pianists with Wearable Motion Detector. In: Stephanidis C., Kurosu M., Degen H., Reinerman-Jones L. (eds) HCI International 2020 – Late Breaking Papers: Multimodality and Intelligence. HCII 2020. Lecture Notes in Computer Science, vol 12424. Springer, Cham. https://doi.org/10.1007/978-3-030-60117-1_15
  • New Atlas. 2022. Music with the Mind: The Brain-Computer-Music-Interface. [online] Available at: <https://newatlas.com/music-with-the-mind-brain-computer-music-interface/18489/>
  • News.ycombinator.com. 2022. As someone who works with EMG, the hype CTRL-Labs has been pushing regarding the… | Hacker News. [online] Available at: <https://news.ycombinator.com/item?id=21061813>
  • Roos, D., 2017. Brain-Computer Interface Allows Users to Compose Music With Only Their Thoughts. [online] Seeker. Available at: <https://www.seeker.com/health/mind/brain-computer-interface-allows-users-to-compose-music-with-only-their-thoughts>
  • Rowntree, D., 2022. PsyLink An Open Source Neural Interface For Non-Invasive EMG. [online] Hackaday. Available at: <https://hackaday.com/2022/01/07/psylink-an-open-source-neural-interface-for-non-invasive-emg/>
  • TEPE, C. and DEMİR, M., 2020. Detection and Classification of Muscle Activation in EMG Data Acquired by Myo Armband. European Journal of Science and Technology, pp.178-183.

Social Un-distancing

Project title: Social Un-distancing

Members: Ellie HUANG, Nooshin MOHTASHAMI

Project Description: 

This project stems from series of discussion derived from us entering the  post-Covid period. During the global pandemic, we are gradually getting used to avoiding physical contact and being increasingly reluctant to step out of our safe distance. While this self-isolation becomes a norm and psychological issues like depression starts to raise significantly emerging from this kind of state, we oftentimes forget about the intrinsic value of social interactions and its significance to us as human beings.

We want to create a social un-distancing reminder which encourages people to make more contacts with fellow humans, and emphasize on the amount of joy and energy we could actually receive from these communications.

This piece of wearable is a pocket light indicator attached to any part of clothing and on the other end connected to a glove. It could be interpreted as an energy reservoir. The way it works is with 10 Neopixels on the board, it invites people to make contact with others by lighting up the Neopixels into red. If within a certain amount of time (currently 5 secs for demonstration purpose) the glove has not being touched anyone else, the red Neopixels will de-color into purple. With a similar gap of time that the glove is not being touched, the Neopixels gradually becomes yellow and then off. However, if within the whole range a next person has been in contact with the wearer, a next Neopixels will be light up into red, indicating another gained energy point. Within full Neopixels being activated, the wearable will blink with a smily face with a piece of joyous music to indicate the completeness of today’s mission of getting in touch with x number of people.

For real life usage, this piece of wearable could be programmed into customizable system that wearer would be able to adjust the total amount of people they want to interact with in a day (set a target number of Neopixels) and the cool off time (e.g. 30 minutes for one degree de-coloring).

Final photos:

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social un-distancing

Parts list:

  1. Adafruit Circuit Playground express
  2. Conductive thread
  3. Conductive fabric
  4. Gloves
  5. Felt
  6. Connection wires
  7. Power bank and USB cord

Circuit Diagram:

wechatimg630

Github Code: 

https://github.com/n00shinm/SocialUndistancing/blob/main/blinkorama.ino 

Project Context:

According to a longitudinal analysis of the COVID-19 Social Study published on Psychological medicine, the inter-relationship between social contact and depression is closely examined “People who were usually more sociable or had higher empathy had more depressive symptoms during enforced reduced contact”(Sommerlad,2021). The result implicated our potential future pandemic actions and the relationship between social factors and mental health.

With technical advances, we would like to create a piece of wearable that nudges users to re-initiate social interactions. Many emerging technologies are enabling individuals to self-manage and to integrate myriad forms of help and support. Currently, there are already numerous products on the consumer markets that could intake full body feedback and output with visual information. For our project, we wanted to create a device that could be rapidly prototyped and enable users in a similar powerful fashion. 

One of the projects that was a great inspiration for our work is The Emotional Clothing collection, which was Węglińska’s doctoral dissertation at the Academy of Fine Arts in Krakow. This project is designed to broaden the experience of clothing and extend fashion vocabulary. Węglińska’s garments react to the wearer’s heart rate, temperature and Galvanic Skin Response (GSR) via sensors, which in turn trigger light changes. Via information gathered from sensors attached to the wearer’s fingers, lights change according to the beat of the wearer’s heart at the sides of the top flash. Since stress usually causes a rise in temperature and a faster heartbeat, this collection of garments output the inner feeling of the users. 

Another project working along a similar line is Halo, which is a networked clothing that each garment has its own microcontroller and light panel. Individual units are able to receive rhythm input from the parent unit with serial and infrared receivers. Thus, one Halo can interact with other Halos and create dynamic visual patterns using this interactivity. In addition to networked interaction, users can provide real-time input for Halo and alter its visual patterns. The emotions can be converted into unique visual statements.

Both two projects incorporate the elements of light and wearable technologies. The visualization of light effects and alterations are both tied with emotions and inner feelings of the users. For the Halo project, users wearing the garment have the active control of altering rendered effects, which provides incentive for users to make actions. This interactivity was also replicated into our project of allowing users to be incentivized of their action choices and be informed with the visual outcomes.

Some other references we have looked at include smaller projects from the adafruit forum: Heart Rate Badge(https://learn.adafruit.com/heart-rate-badge), Circuit Playground Wearable(https://learn.adafruit.com/circuit-playground-wearable), Chatty Light-Up Circuit Playground Express Mask(https://learn.adafruit.com/chatty-light-up-cpx-mask). These projects greatly informed us in diverse ways about modes of fabrication and material choices. In constructing our wearable pieces, we have experimented with different formats of physical containers for the Adafruit Playground. From one of the above sources – Circuit Playground Wearable, we referenced their 3D printing models and tested them as one of our design iterations. Despite not taking the watch format as our final rendering, we have enhanced our proficiency via those trials and errors.

Progress Photos/iterations:

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Next Step:

For real life applications, we would love to enhance the customizability of this wearable piece. Users would be able to extend the time of cooling down accordingly. The program could further be enhanced by allowing the users to input their ideal number of interactions in a day, thus people who are more introverted do not need to meet a high goal set for extrovert people. For future development, this wearable could be better integrated into the whole piece of garment with minimal visibility – aligning with principles of calm technology.

References:

  • Ada, L., 2017. Adafruit Circuit Playground Express. [online] Adafruit Learning System. Available at: <https://learn.adafruit.com/adafruit-circuit-playground-express>
  • Brothers, R., 2016. Circuit Playground Wearable. [online] Adafruit Learning System. Available at: <https://learn.adafruit.com/circuit-playground-wearable>
  • Ceceri, K., 2020. Chatty Light-Up Circuit Playground Express Mask. [online] Adafruit Learning System. Available at: <https://learn.adafruit.com/chatty-light-up-cpx-mask>
  • Couto, R., 2019. Songs for Arduino – Dragão sem Chama. [online] Dragão sem Chama. Available at: <https://dragaosemchama.com/en/2019/02/songs-for-arduino/>
  • FancourtD.SteptoeA., & BuF., 2020Trajectories of anxiety and depressive symptoms during enforced isolation due to COVID-19 in England: a longitudinal observational studyLancet Psychiatry, S2215-0366(20)30482-X.
  • Mura, G., 2008. WEARABLE TECHNOLOGIES FOR EMOTION COMMUNICATION. [online] Academia.edu. Available at: <https://www.academia.edu/849549/WEARABLE_TECHNOLOGIES_FOR_EMOTION_COMMUNICATION>
  • Stern, B., 2013. Heart Rate Badge. [online] Adafruit Learning System. Available at: <https://learn.adafruit.com/heart-rate-badge>
  • Zhang, Y., 2020. Flower Wheel – Spring Show 2020. [online] Itp.nyu.edu. Available at: <https://itp.nyu.edu/shows/spring2020/flower-wheel/>
  • Sommerlad, Andrew, et al. “Social Relationships and Depression during the COVID-19 Lockdown: Longitudinal Analysis of the COVID-19 Social Study.” Psychological Medicine, 2021, pp. 1–10., doi:10.1017/S0033291721000039.