Ausculo
ConceptA digital stethoscope for telemedicine in rural India — designed so a community health officer with no specialist training can capture a chest sound a remote doctor will trust.
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- My role
- Sole designer — research, hardware form, UI
- Organisation
- CARE, IIT Delhi (B.Des thesis, NID Ahmedabad)
- Timeline
- 2024 · ~6 months
- Status
- Concept — reached testing, not production
Published
Poddar, L., Koruprolu, V. S., Shaikh, M. N., & Aggarwal, M. (2025). Digital Stethoscopes for Telemedicine in Rural India: Designing for Usability and Practical Adoption. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. doi:10.1177/10711813251364797
At a glance
What this was, and where it stopped
India's public telemedicine platform, eSanjeevani, connects rural health centres to city doctors by video. But a video call cannot auscultate — a doctor cannot listen to a chest through it, and auscultation is first-line for respiratory and cardiac screening. Ausculo set out to close that gap with a device cheap and simple enough to actually reach a rural health centre.
I joined an existing hardware effort at CARE, IIT Delhi as its only designer, and owned research, the physical form, and the interface. Heart-health diagnostics is a subject I came to for personal reasons, which is a large part of why I stayed with it.
The work reached validated concept stage and was published at HFES 2025. It did not ship — the electronics were not ready to support the interface I had designed. I have kept that framing here rather than implying a launch.
37
Research participants, urban + rural
33
Forms ranked by clinicians
₹6–7k
Target price vs ₹27k+ incumbents
2
Field rounds — Delhi, Dharamshala
01 — Problem
Doctors were being asked to diagnose with a sense removed
Most of India lives in villages; most specialists work in cities. eSanjeevani's hub-and-spoke model bridges that by putting a Community Health Officer at the "spoke" — a Health & Wellness Centre — and a doctor at the hub. It works for consultation and triage. It fails the moment the doctor needs to hear something.
Cardiovascular disease accounts for roughly 28% of all deaths in India (WHO), and it is precisely the category where a chest sound changes the decision. Digital stethoscopes that could transmit audio already existed — they just had not reached rural India, and the reason was mostly price.
₹27,543
3M Littmann CORE
₹33,404
Eko CORE 500
₹6–7k
What our users would pay
That last figure was not a guess. Interviews produced a clear willingness-to-pay ladder: ₹500–2,000 for medical students, ₹2,000–5,000 for MBBS doctors, ₹15,000+ only for established specialists. The brief I inherited assumed a ₹15,000 device. For the users it claimed to serve, that was already out of reach.

02 — The reframe
The brief named the wrong user
The project I inherited assumed ASHA workers would carry the stethoscope into villages. It was a reasonable-sounding assumption, and it was wrong.
The assumption
What research showed
I re-targeted the primary user to CHOs, with medical students as a secondary group (recording and replaying sounds has obvious teaching value). This one change cascaded through everything downstream — the interface, the training aids, the price ceiling, and what "simple enough" had to mean.
Why this mattered most
03 — Research
Getting to 37 participants when doctors won't talk to you
Doctors were genuinely hard to reach — rarely free during working hours, and unresponsive without a personal referral. That constraint shaped the method: I could not shadow or run long interviews, so I built approaches that fit the access I actually had.
- Secondary sweep — papers, plus Reddit, Twitter, LinkedIn groups and YouTube reviews, because Amazon and Google Trends only yielded generic feedback.
- Stakeholder interviews — doctors, medical students, ASHA workers, CHOs and telemedicine startups.
- Stanford BioDesign — disease-state analysis across respiratory, cardiovascular, gastrointestinal, obstetric and vascular auscultation.
- Competitive teardown — I bought and dismantled a Littmann CORE.
- Expert sessions — Dr. Desh Deepak (Pulmonology, RML Hospital) and Dr. Sanjay Sood (Director, eSanjeevani).
What each group actually said
Doctors
Deeply habituated to the analog form. Several who owned digital stethoscopes had stopped using them. Many were sceptical of telemedicine itself — blurred boundaries, diagnostic ambiguity, and no clear accountability for a remote call.
Medical students
The most receptive group — still forming habits, so nothing to unlearn. They asked for noise cancellation and clearer audio cues, then balked hard at ₹15,000.
ASHA workers
Almost none had used a digital stethoscope. Their concern was not the device but the system around it: a new tool means more work, without more pay, on top of a load already stretched thin.
The teardown was the most useful hour
Taking apart a ₹27,543 Littmann CORE surfaced problems no spec sheet lists. It took over 2.5 hours to charge and lasted 8 hours — not enough for an Indian hospital shift. Sound amplification amplified the rubbing of the chestpiece into something shrill. Worst of all was the workflow: you wear the stethoscope, then pick up your phone, then open the app, then re-pair it, and only then can you listen. Both hands are already occupied.






04 — Constraints
The non-negotiables
Context, not features, was the only real differentiator available. Eko and Littmann already had noise cancellation and AI murmur detection. What they did not have was a device that survives a rural Health & Wellness Centre.
Cost
₹6–7k ceiling — a quarter of the incumbents
Power
Standard AA/AAA — no charging infrastructure
Connectivity
Must degrade to offline, or to a phone call
Training
Semi-trained users, language barriers
Durability
Field conditions, minimal maintenance
Integration
Must fit eSanjeevani's existing flow
Standards
IEC 62366, ISO 14971, IEC 60601
Acoustics
Vesicular <100Hz to tracheal 400–600Hz
05 — Decisions
Seven decisions, including two that failed
The two rejected hypotheses below are here deliberately. Both were things I believed, built, tested, and abandoned — which is the part of the process that actually moved the design.
Re-target the primary user from ASHA workers to Community Health Officers
- Why
- Auscultation is not in ASHA training; CHOs are the ones who actually staff Health & Wellness Centres and run eSanjeevani consultations.
- Tradeoff
- Narrowed the addressable user base and abandoned research time already spent with ASHA workers.
- Evidence
- Confirmed with Dr. Sanjay Sood, Director of eSanjeevani; corroborated against ASHA training curricula.
Switch from piezoelectric sensors to MEMS
- Why
- The piezo sensor alone cost ₹5,000 — impossible inside a ₹6–7k device. MEMS are small, mass-producible and stable across conditions.
- Tradeoff
- Forced a complete enclosure redesign mid-project, and collapsed the architecture from two PCBs plus a DAC board to a single PCB.
- Evidence
- Bill-of-materials costing against the price ceiling derived from interviews.
Keep two sensors for adaptive noise cancellation
- Why
- Body-movement noise sits at a similar amplitude to heart sounds, so it cannot be filtered by threshold. A second sensor captures ambient noise so it can be subtracted from the primary signal.
- Tradeoff
- More cost and board area than a single-sensor design, against a hard cost ceiling.
- Evidence
- The teardown showed amplification also amplifies chestpiece rub into something painful to listen to.
Make the device work standalone, not tethered to a phone
- Why
- Auscultation occupies both hands. Any flow that requires picking up a phone mid-examination will not be followed.
- Tradeoff
- On-device controls and feedback mean more hardware cost than offloading the interface to an app.
- Evidence
- Directly observed while using the Littmann CORE: wear, retrieve phone, open app, re-pair, then listen.
Split the interface for doctors and CHOs instead of one shared UI
- Why
- Field testing showed the features doctors need are useless to a CHO, and their presence made the CHO's job harder.
- Tradeoff
- Two interfaces to design and maintain rather than one.
- Evidence
- Dharamshala testing round — the finding that changed the interface direction.
Rejected: a protective cap over the sensors
- Why
- I assumed the sensors needed shielding from direct skin and hand contact, and built a flexible cap from a 3D-printed mould.
- Tradeoff
- None worth taking — testing showed the cap damped the signal it was meant to protect.
- Evidence
- Bench testing, then confirmed with the sensor manufacturer: direct contact is preferable. The assumption was mine, not theirs.
Rejected: a horn-shaped waveguide to concentrate vibration
- Why
- Hypothesised that tubing broad at the top and narrow at the bottom would funnel more chest vibration into the sensors.
- Tradeoff
- Cost prototype cycles that produced no gain.
- Evidence
- Measured no improvement — the sensors are designed to take vibration directly, so there was nothing for the horn to add.
06 — Quantitative study
Ranking 33 forms with a chess algorithm, on a tool I built
Doctors could not articulate a form preference in the abstract, and asking them to rate designs on a scale produces answers that shift with whatever they saw last. So I ran a forced-choice pairwise study instead — and had to solve two problems to make it fit inside the access I had.
33
Candidate designs
528
Comparisons if exhaustive
28
Actual comparisons per session
10 days
To build the ranking tool
Problem one: too many pairs. A full round-robin across 33 designs is 528 comparisons — nobody sits through that. I grouped the comparisons using a merge-sort–style divide-and-conquer scheme, which brought each session down to 28 while still producing a global ordering.
Problem two: scoring. I used the Elo rating system from chess, so each design's score updates against the strength of what it beat. Elo also sidesteps the independence-of-irrelevant-alternatives problem that rating scales suffer from, and it keeps the respondent's task down to one question: this or that.
No off-the-shelf tool did this, so I built the ranking site myself in 10 days, capturing each respondent's specialty, city, age and institution type alongside their choices.
Results — Elo 1154 to 1664
Getting there took a dead end first. I kept refining techno-aesthetic detailing and every result still looked like every other stethoscope on the market. The break came from chess piece geometry — clean, gripped, visually distinct — which I then printed and hand-tested for ergonomics rather than trusting the render.




Constraint mapping, form variants, and printed candidates hand-tested for grip — the enclosure had to hold two PCBs 3cm apart while leaving the sensor face in direct contact.
To add — Elo results visualisation
The full 33-design ranking with scores and the age/gender/institution splits deserves a chart rather than prose. Raw scores are in the thesis (pp. 301–303).
07 — Validation
Two field rounds, and an honest limit on the data
Delhi — moderated think-aloud sessions with doctors. I asked participants to narrate what they were thinking, and set a completion time deliberately to add pressure, on the theory that mild stress exaggerates the friction you are trying to see.
Dharamshala — the round that mattered. Dharamshala itself is not remote, but the areas around it are, and it has a real density of PHCs and sub-centres. Access came through a contact who knew the CMO, Dr. Rajesh Guleri. The trip was not funded; I paid for it because testing a rural device anywhere else felt indefensible.
Because I had no fully working device, sessions ran as role-play: a CHO would place the stethoscope, take instruction from a remote doctor and work through recording, while doctors imagined reviewing the audio against a patient record. I gave participants a simplified heuristic checklist — visibility of system status, match to the real world, user control — and asked them to flag anything missing or unclear.
A limitation worth stating plainly


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To add — SUS scores
Sessions closed with a System Usability Scale survey to set a baseline, but the scored results are not in Volume 1 of the thesis and were never written into the process documentation. Add the numbers, or state that the baseline was indicative only.
08 — Outcome
What the testing changed
Power
Proprietary and rechargeable packs out; standard AA/AAA in, so a cell can be replaced anywhere off-grid.
Connectivity
Fallback to basic phone-call audio transmission where there is no usable internet.
Interface
Language-neutral cues plus audio playback, for semi-trained users facing training and language barriers.
Training aids
Error detection, slow-motion playback and instructional diagrams built into the device rather than a separate manual.
Integration
Compatibility with eSanjeevani, and with DocOn and Practo, so it fits clinical routine instead of replacing it.
Autonomy
A self-contained mode that does not depend on a phone or tablet being present and charged.
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To add — Final feature and control list
The resolved concept's modes, on-device controls and interface behaviour exist only as images in the thesis (pp. 316–319). Write them out as a spec here.
To add — Interface screens
Capture, playback and sharing flows — plus the split doctor/CHO interfaces from decision 05 — are the biggest missing artifact on this page.
To add — Journey map and audio benchmarks
The in-person vs remote journey map, the clinical workflow diagram, and any audio quality measurements against the 100–600Hz auscultation bands.
09 — Reflection
What I'd do differently
What worked
What I'd change
What I learned
The device did not ship. The research did — as a published paper, a validated form direction, and a mapped integration path for whoever picks it up next.