2014 · IEEE journal of biomedical and health informatics · paywalled
A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors
Yousefi et al.
The finding, in our words
The authors developed a two-stage adaptive noise-cancelling algorithm that extracts heart rate and oxygen saturation from wearable photoplethysmographic biosensors despite motion artefact. Validation against commercial reference sensors during standing, walking and running showed correlations exceeding 0.98 for heart rate and 0.7 for SpO2, demonstrating robust performance in real-world movement conditions.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
The study observed favourable trends in the accrual of participants residing far from the site and those from underrepresented groups following the implementation of a decentralised clinical trial program.
This review establishes that microsampling across blood, saliva, urine and stool matrices offers validated workflows and regulatory recognition for human biomonitoring comparable to conventional methods. It finds that these decentralised approaches enhance participant acceptability and enable screening in remote or low-resource settings.
This study demonstrates that a memristor sensor can identify distinct electrical signatures in saliva and urine corresponding to different ovulation phases, suggesting a potential route for noninvasive home fertility monitoring.
Menstrual blood offers a noninvasive, patient-centric matrix for detecting endometriosis, cervical cancer, and hormonal disorders through self-collected samples. Wearable in-pad biosensors enabling real-time monitoring and long-term tracking could transform fertility evaluation and early disease detection, though standardisation and large-scale validation remain critical gaps.
Shafiq et al., Annals of medicine and surgery · source ↗
A fully remote decentralised clinical trial in Danish adults with type 2 diabetes demonstrated operational feasibility with rapid recruitment, high retention (87 percent), and excellent adherence to continuous glucose monitoring (95 percent achieving ≥70 percent data coverage) and telemedicine visits (97 percent). Activity tracker adherence was poor (12 percent) due to technical issues, but remote safety monitoring was effective with no unexpected adverse events, supporting the viability of remote diabetes management.