Findings
SV95C provides a reliable and sensitive measure of maximal ambulation, addressing limitations of traditional assessments like the 6MWT.
Real-world data collection via wearable devices enhances accuracy and reflects true ambulatory capabilities.
Longitudinal studies confirmed SV95C's ability to detect disease progression and response to corticosteroid treatments.
Correlations with existing clinical outcome assessments (6MWT, NSAA, and 4SC) validate SV95C’s construct validity.
Patients and caregivers support the use of wearable devices in clinical trials, emphasizing reduced burden and improved trial attractiveness.

Recommendations
Use SV95C as a primary endpoint in DMD clinical trials to monitor maximal stride velocity in real-world conditions.
Incorporate SV95C alongside traditional endpoints to ensure comprehensive assessment of therapeutic efficacy.
Establish training protocols for patients and caregivers to optimize compliance with device usage.
Expand normative data for SV95C in younger and more diverse patient populations.
Conduct further research on meaningful change thresholds (MCTs) to refine clinical relevance.

Regulatory Considerations
Ensure SV95C is included as a primary endpoint with supporting secondary endpoints (e.g., muscle strength assessments) for consistency.
Validate wearable devices used for SV95C measurement to meet regulatory standards for accuracy and reliability.
Address variability and standardize protocols for data collection to ensure regulatory compliance.
Collect additional longitudinal data to strengthen the predictive value of SV95C for regulatory submissions.
Incorporate privacy and data security measures to comply with data protection regulations, including anonymization and encryption.

Findings
Sensor-generated health data must be collected in a way that ensures completeness, contextual metadata, and fit-for-purpose accuracy to support clinical applications.
Data security and privacy regulations vary globally, necessitating the implementation of adaptable frameworks such as the FAIR data principles and cybersecurity best practices.
Standardized data transmission and processing protocols are required to ensure interoperability across digital health platforms and prevent data loss or corruption.
Validation frameworks, such as DiMe’s V3 (Verification, Analytical Validation, and Clinical Validation), are essential to confirm the reliability of digital clinical measures.
Equity and accessibility considerations must be prioritized, ensuring that digital health solutions work across diverse populations and healthcare settings.

Recommendations
Digital health developers should follow standardized methodologies for data collection, leveraging frameworks such as the EVIDENCE checklist and DiMe’s V3 validation process.
Privacy-by-design principles should be embedded into sensor-based data systems to comply with HIPAA, GDPR, and emerging digital health privacy regulations.
Data processing workflows must be transparent, well-documented, and validated to ensure consistent, unbiased, and reproducible results in clinical applications.
Organizations should adopt cybersecurity best practices, including end-to-end encryption, authentication protocols, and risk mitigation strategies, to protect sensor data.
Sensor data integration strategies should be aligned with industry standards and open-source protocols to promote interoperability and scalability in healthcare ecosystems.

Regulatory Considerations
Regulatory agencies such as the FDA encourage the use of validated digital biomarkers and structured sensor data processing methodologies to support regulatory submissions.
Sensor data privacy policies must comply with local and international regulations, requiring clear user agreements, informed consent, and transparent data governance.
Secure data transmission protocols must be implemented to prevent unauthorized access, aligning with industry standards for encryption, authentication, and network security.
Organizations deploying sensor-based health technologies should conduct risk assessments and audits to ensure compliance with evolving regulatory requirements for AI and digital health.
Global harmonization of data security and transmission standards is necessary to support cross-border data exchange, facilitating regulatory approval and market access for digital health innovations.

Findings
There is a gap in developing robust and meaningful outcome measures based on DHTT sensor data.
A major challenge is integrating vast amounts of sensor data into meaningful clinical outcome measures.
There is no clear pathway for developing these outcome measures, indicating a need for standardized methods.

Recommendations
Develop roadmaps for data-centric and patient-centric digital outcome measures.
Integrate patient insights into the development of outcome measures.
Ensure statistical robustness and validity in digital outcome measures.
Encourage scientific discourse to reach a consensus on digital outcome measure development.
Combine subjective and objective data for comprehensive patient assessment.

Regulatory Considerations
The field relies on guidance from regulatory authorities like the FDA and EMA.
Regulatory frameworks need to keep pace with the fast-moving nature of DHTTs.
There is a need for consensus on digital outcome measure development that respects established methods.

Findings
SV95C is a promising secondary endpoint for evaluating drug efficacy in ambulant DMD patients aged 5 and above.
The wearable device provides continuous, objective measurements, overcoming the limitations of episodic tests like the 6MWT, which are influenced by patient motivation and clinic settings.
The system demonstrates strong correlation with existing endpoints (e.g., 6MWT, NSAA), but further longitudinal data are needed to establish it as a primary endpoint.
Variability in SV95C decreases significantly with longer recording durations, with 180 hours recommended as optimal.
Combining SV95C with other gait variables could enhance sensitivity to change and predictive capacity for disease progression.

Findings
SV95C is a promising secondary endpoint for evaluating drug efficacy in ambulant DMD patients aged 5 and above.
The wearable device provides continuous, objective measurements, overcoming the limitations of episodic tests like the 6MWT, which are influenced by patient motivation and clinic settings.
The system demonstrates strong correlation with existing endpoints (e.g., 6MWT, NSAA), but further longitudinal data are needed to establish it as a primary endpoint.
Variability in SV95C decreases significantly with longer recording durations, with 180 hours recommended as optimal.
Combining SV95C with other gait variables could enhance sensitivity to change and predictive capacity for disease progression.

Regulatory Considerations
SV95C requires validation in conjunction with traditional endpoints (e.g., 6MWT, NSAA) to support regulatory submissions.
Device and software updates must be accompanied by bridging data to ensure consistent measurement properties.
Patient data privacy and security must comply with regulatory standards, including encryption of recorded data and limited researcher access to identifiers.
Future applications of SV95C as a primary endpoint will require expanded normative datasets and stronger correlation with clinically meaningful outcomes.
Incorporate SV95C in early-phase exploratory trials to build a robust case for its clinical relevance in pivotal studies.