Dataset opportunity
Motusnova — Sensor Telemetry Dataset Opportunity
Large sensor telemetry dataset held by Motusnova, usable for Predictive Maintenance and Anomaly Detection.
Score
71.3
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
65%
Action
Data Sharing Agreement
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market
Global Predictive Maintenance Market = $14.93 Billion in 2025, CAGR 32.32% (2026-2035)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-02
Petal Surgical adds more funding for incisionless surgical robot
therobotreport.com ↗ - 📰press2026-05-29
J&J recalls Impella heart pumps after patient dies
medtechdive.com ↗ - 📰press2026-05-28
Ōura to add blood pressure feature following FDA policy change
medtechdive.com ↗
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Profile
Dataset profile
Type
Sensor Telemetry Dataset
Modality
Time Series
Sector
healthcare
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
Industrial AI & maintenance-optimization vendors
Motusnova possesses a unique Sensor Telemetry Dataset, primarily in a Time Series modality, encompassing extensive IoT data and medical records. This rich collection is exceptionally well-suited for Predictive Maintenance applications, enabling the anticipation of equipment failures and optimization of maintenance schedules in critical healthcare environments.
The market for predictive maintenance, particularly in healthcare, is experiencing significant growth, with the global Predictive Maintenance Market valued at $14.93 billion in 2025 and projected to reach $245.73 billion by 2035, demonstrating a remarkable 32.32% CAGR. Despite complexities involving Patient Health Information (PHI), regulatory compliance (HIPAA/GDPR), and consent management, the data's value for enhancing patient safety, reducing downtime, and improving operational efficiency makes it highly sought after by AI buyers. ⚠ Diligence (valuable data, access to negotiate): Patient health data (PHI); Regulatory compliance (HIPAA/GDPR); Consent management for secondary data use · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Motusnova possesses a proprietary, high-resolution time series dataset derived from 3,000+ deployed medical devices used by thousands of stroke survivors. This unique telemetry, capturing real-world device performance and patient interaction, offers unparalleled insights for AI buyers focused on predictive maintenance and optimization. With the Global Predictive Maintenance Market projected to reach $14.93 Billion by 2025, this dataset is exceptionally valuable for developing advanced models that enhance device reliability and user outcomes in a rapidly expanding sector. Its rarity and direct relevance to industrial AI applications make it a compelling opportunity now.
See dimension details ↓- Dataset Specificity90
dominant 'iot_data', sector healthcare, 3 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume86
6 evidence hits, explicit data-volume mention
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Predictive Maintenance
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand95
The global AI in healthcare market, which includes AI data buyers for applications like predictive maintenance, is projected to grow at a CAGR of 37.1% from 2024 to 2032, indicating very high and increasing demand for relevant datasets.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/regulated
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
high difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength89
5 evidence types, 6 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
ownership=mixed, licensing=gdpr_sensitive
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 data-appetite signals (0 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 3 recent external signals — proprietary data beyond what's already monetised
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit75
⚠ review — Motusnova's core business is selling AI-powered robotic rehabilitation devices that provide personalized therapy and reports, which constitutes selling intelligence derived from proprietary data, making them an unsuitable target for dormant data. Issues: Motusnova's core business is selling AI-powered rehabilitation devices and the intelligence (personalized therapy, adaptive exercises, progress reports) derived
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
This evidence confirms the collection of high-resolution sensor telemetry (angle, pressure) at 30 readings per second from Motus Hand/Foot devices during therapy, stored in a time series database and paired with stroke residual severity labels, offering critical data for predictive analytics on device performance and patient progress.
Industrial data
This evidence highlights the holder's leadership having board-level experience in diverse industrial sectors, suggesting a foundational understanding of operational excellence and large-scale data management relevant to industrial AI applications.
Knowledge base / docs
This indicates access to patient enrollment data and clinician-informed insights, providing valuable contextual information for understanding user demographics and program adherence in a healthcare setting.
Medical records / imaging
This demonstrates the devices' efficacy across a diverse patient population (varying stroke severity, post-stroke duration, ages), providing crucial context for understanding the real-world applicability and impact of the collected sensor data.
Data-volume signal
This confirms a substantial deployment of 3,000+ devices across all 50 states, used by thousands of stroke survivors, establishing a significant and proven real-world dataset for robust AI model training and validation.
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series, IoT Data
License
One-time license for predictive maintenance use cases, with potential restrictions on redistribution or resale.
Personal data
Contains PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's value is driven by its high rarity, proprietary nature, and direct application to the rapidly growing healthcare predictive maintenance market. The significant market growth and CAGR indicate strong demand for such specialized, real-time telemetry.
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Motusnova Sensor Telemetry — a Large sensor telemetry dataset (Time Series modality) in the healthcare domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance Market = $14.93 Billion in 2025, CAGR 32.32% (2026-2035). Investment score 71.3/100 (confidence 0.65). Recommended action: Data Sharing Agreement.
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