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Instead of showing the images, each frame is reduced to simple descriptors that drive analog oscillators, whose patterns appear on a vintage oscilloscope. A machine-learning captioning module and a visitor-tracking camera feed two CRT monitors, completing the loop.",{"type":47,"tag":56,"props":70,"children":71},{},[72],{"type":53,"value":73},"Using offline analog hardware is deliberate: its signals cannot be stored or tracked. 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Rather than displaying the images, each frame is reduced to three quantitative descriptors—edge density, luminance variance, and dominant hue—which are converted into control voltages that drive analog oscillators. Their signals form shifting patterns on a vintage laboratory oscilloscope, revealing the data as pure electricity.\n    ",{"type":53,"value":96},{"type":47,"tag":56,"props":303,"children":304},{},[305],{"type":53,"value":306},"\n      A second module uses a local machine-learning model to caption what the algorithm “sees” in each unseen frame. These captions appear on a CRT monitor, exposing only the system’s interpretation—never the source image.\n    ",{"type":53,"value":96},{"type":47,"tag":56,"props":309,"children":310},{},[311],{"type":53,"value":312},"\n      A third module employs an on-site camera to track visitors. This data modulates noise and subtle sonic textures, integrating the audience into the feedback loop. 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We routinely trade privacy for convenience, often without knowing who is watching or how our data will be used. ",{"type":47,"tag":230,"props":416,"children":417},{},[418],{"type":53,"value":9},{"type":53,"value":420}," uses reality as raw material.",{"type":47,"tag":141,"props":422,"children":424},{"id":423},"concept",[425],{"type":53,"value":426},"### Concept",{"type":47,"tag":56,"props":428,"children":429},{},[430,432,446],{"type":53,"value":431},"Working with analog hardware, the piece captures live feeds from publicly accessible surveillance cameras worldwide (watchingtheworld project ",{"type":47,"tag":433,"props":434,"children":435},"sup",{},[436],{"type":47,"tag":437,"props":438,"children":443},"a",{"href":439,"ariaDescribedBy":440,"dataFootnoteRef":8,"id":442},"#user-content-fn-1",[441],"footnote-label","user-content-fnref-1",[444],{"type":53,"value":445},"1",{"type":53,"value":447},"). Each frame is reduced to measurable parameters—color, luminance, edge density—which are transformed into control voltages that trace moving patterns on a laboratory oscilloscope. In parallel, a local machine-learning model generates textual captions of what the algorithm “sees,” projected onto a CRT monitor. Visitors therefore hear the data through sound and read algorithmic interpretations, but never see the original images.",{"type":47,"tag":56,"props":449,"children":450},{},[451],{"type":53,"value":452},"A second module uses an on-site webcam to capture visitor pose. This data modulates the background noise on the monitor and alters the sonic texture, creating granular shifts that make the audience a live participant in the system. 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By remaining offline, the devices in this artwork act as rebellious outcasts—refusing assimilation into the seamless circuits of data capture. The result is an analog loop that resists storage, resists transmission, and returns to technology’s physical origins: electricity, signal, noise.",{"type":47,"tag":141,"props":470,"children":472},{"id":471},"distortion",[473],{"type":53,"value":474},"### Distortion",{"type":47,"tag":56,"props":476,"children":477},{},[478],{"type":53,"value":479},"By translating images into voltages, the work speaks in the language of the machine: electricity. What returns from that current is never the world itself but an algorithmic distortion—a partial, fragmented version of reality. The installation makes this gap tangible: visitors witness how the machine reconstructs only pieces of the world, presenting not truth but data-driven representation. In exposing electricity as medium and reduction as method, the piece invites reflection on who controls the narrative and what is lost when machines mediate our experience.",{"type":47,"tag":141,"props":481,"children":482},{"id":8},[483],{"type":53,"value":484},"### …",{"type":47,"tag":56,"props":486,"children":487},{},[488,490,494],{"type":53,"value":489},"Ultimately, ",{"type":47,"tag":230,"props":491,"children":492},{},[493],{"type":53,"value":9},{"type":53,"value":495}," is an analog rebellion—a work that confronts audiences with the politics embedded in data collection and machine vision, and asks them to reckon with the systems that watch, classify, and shape their lives.",{"type":47,"tag":373,"props":497,"children":498},{},[],{"type":47,"tag":500,"props":501,"children":504},"section",{"className":502,"dataFootnotes":8},[503],"footnotes",[505,512],{"type":47,"tag":48,"props":506,"children":509},{"className":507,"id":441},[508],"sr-only",[510],{"type":53,"value":511},"Footnotes",{"type":47,"tag":513,"props":514,"children":515},"ol",{},[516],{"type":47,"tag":186,"props":517,"children":519},{"id":518},"user-content-fn-1",[520,527,529],{"type":47,"tag":437,"props":521,"children":525},{"href":522,"rel":523},"https://webcamaze.engineering.zhaw.ch",[524],"nofollow",[526],{"type":53,"value":522},{"type":53,"value":528}," ",{"type":47,"tag":437,"props":530,"children":535},{"href":531,"ariaLabel":532,"className":533,"dataFootnoteBackref":8},"#user-content-fnref-1","Back to reference 1",[534],"data-footnote-backref",[536],{"type":53,"value":537},"↩",{"title":8,"searchDepth":539,"depth":539,"links":540},2,[541,542,543,545,546,547,554],{"id":50,"depth":539,"text":54},{"id":213,"depth":539,"text":216},{"id":227,"depth":539,"text":544},"In detail: Max/MSP Patch – Oscilloscope Simulation",{"id":280,"depth":539,"text":283},{"id":329,"depth":539,"text":332},{"id":378,"depth":539,"text":381,"children":548},[549,551,552,553],{"id":423,"depth":550,"text":426},3,{"id":460,"depth":550,"text":463},{"id":471,"depth":550,"text":474},{"id":8,"depth":550,"text":484},{"id":441,"depth":539,"text":511},"markdown","content:projects:analog-resistance.md","content","projects/analog-resistance.md","projects/analog-resistance","md",{"_path":562,"_dir":6,"_draft":7,"_partial":7,"_locale":8,"title":563,"description":564,"subtitle":565,"year":566,"featured":7,"cover":567,"source":568,"category":14,"tags":569,"location":571,"event":572,"stills":573,"media":589,"body":596,"_type":555,"_id":722,"_source":557,"_file":723,"_stem":724,"_extension":560},"/projects/nexus-science-through-sound","Nexus – Exploring Science Through Sound","Presented during the Renaissance transdisciplinary exhibition at Le Commun (Geneva), 2–25 June 2022.","Neural electrophysiology data transformed into an immersive sound piece",2022,"/images/nexus/52206222719-e44d4eb0b9-cover.webp","https://pedroespinosa.ch/projects/nexus-science-through-sound",[570,17,18],"neuroscience","Le Commun, Genève","Renaissance (transdisciplinary exhibition)",[574,577,580,583,586],{"src":575,"alt":576},"/images/nexus/neurona-pedro-3-2.webp","Nexus – installation detail",{"src":578,"alt":579},"/images/nexus/img-7197-mp4-00-09-46-25-still001.webp","Nexus – performance still",{"src":581,"alt":582},"/images/nexus/presentation-004.webp","Nexus – presentation slide",{"src":584,"alt":585},"/images/nexus/img-3613.webp","Nexus – exhibition photograph",{"src":587,"alt":588},"/images/nexus/img-3381-mov-00-00-39-28-still001.webp","Nexus – neuronal microscopy image",[590,593],{"src":591,"alt":592},"/images/nexus/306e5f11-73d3-4c8b-b67d-83041951e5f5.webp","Nexus installation at Le Commun",{"src":594,"alt":595},"/images/nexus/renaissance-flyer.webp","Renaissance exhibition flyer",{"type":44,"children":597,"toc":714},[598,605,609,619,624,629,634,639,645,659,665,670,676,679,682,688,706,711],{"type":47,"tag":56,"props":599,"children":600},{},[601],{"type":47,"tag":62,"props":602,"children":603},{},[604],{"type":53,"value":564},{"type":47,"tag":48,"props":606,"children":607},{"id":50},[608],{"type":53,"value":54},{"type":47,"tag":56,"props":610,"children":611},{},[612,617],{"type":47,"tag":62,"props":613,"children":614},{},[615],{"type":53,"value":616},"N-Plexus",{"type":53,"value":618},", the sound piece at the heart of this project, transforms neuronal recordings into an immersive auditory experience, preserving the analog essence of electrophysiology. Created solely with an analog electrophysiological amplifier, it captures and amplifies neuronal activity, converting voltage fluctuations directly into sound. Aside from subtle reverb and panning, every recording is unaltered — a raw and authentic glimpse into real experimental sessions.",{"type":47,"tag":56,"props":620,"children":621},{},[622],{"type":53,"value":623},"This piece was created during my PhD in Neurosciences, drawing on the auditory tradition of electrophysiology. In the 1970s, before the advent of advanced microscopy, researchers relied on sound to guide electrodes through brain tissue and detect neuronal activity. Modern automation has largely replaced these auditory cues, though some amplifiers still retain a sound output as a nod to that legacy.",{"type":47,"tag":56,"props":625,"children":626},{},[627],{"type":53,"value":628},"N-Plexus revisits that tradition by recording full experimental sessions from start to finish. The piece opens with the static crackle produced as I manually position the electrodes — a sound shaped by the friction between my hands and the equipment. As the electrode travels from air into the solution bathing the brain tissue, abrupt pitch shifts trace its descent.",{"type":47,"tag":56,"props":630,"children":631},{},[632],{"type":53,"value":633},"Once inside the tissue, the analog device behaves like an oscillator modulated by neuronal membranes, bending voltage into a shifting palette of textures. 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