Table 2.

mHealth challenges and solutions

Challenge	Example	Potential solution
Accuracy	No universal baseline	Compare patients to themselves over time as oppose to preset standards
Security	Signal eavesdropping/hacking	Higher level encryption, identification based on personalized physiology parameters (such ECG waveform matching)
Privacy	Loss of confidential data	Restriction to de-identified data to cloud, or use of HITECH/HIPAA compliant cloud server
Investigator practices	Need for expertise from various scientific displaces (medicine, behavioral science, engineering, computer science)	“Team Science” approach, specific focus on interdisciplinary communication strategies
Patient responses	Behavior modification due to the presence of tech	Ecological momentary assessment, placebo controlled clinical trials