TY - JOUR
T1 - Opportunities for smartphone sensing in E‐Health research
T2 - a narrative review
AU - Kulkarni, Pranav
AU - Kirkham, Reuben
AU - McNaney, Roisin
N1 - Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/5/20
Y1 - 2022/5/20
N2 - Recent years have seen significant advances in the sensing capabilities of smartphones, enabling them to collect rich contextual information such as location, device usage, and human activity at a given point in time. Combined with widespread user adoption and the ability to gather user data remotely, smartphone‐based sensing has become an appealing choice for health research. Numerous studies over the years have demonstrated the promise of using smartphone‐based sensing to monitor a range of health conditions, particularly mental health conditions. However, as research is progressing to develop the predictive capabilities of smartphones, it becomes even more crucial to fully understand the capabilities and limitations of using this technology, given its potential impact on human health. To this end, this paper presents a narrative review of smartphone-sensing literature from the past 5 years, to highlight the opportunities and challenges of this approach in healthcare. It provides an overview of the type of health conditions studied, the types of data collected, tools used, and the challenges encountered in using smartphones for healthcare studies, which aims to serve as a guide for researchers wishing to embark on similar research in the future. Our findings highlight the predominance of mental health studies, discuss the opportunities of using standardized sensing approaches and machine‐learning advancements, and present the trends of smartphone sensing in healthcare over the years.
AB - Recent years have seen significant advances in the sensing capabilities of smartphones, enabling them to collect rich contextual information such as location, device usage, and human activity at a given point in time. Combined with widespread user adoption and the ability to gather user data remotely, smartphone‐based sensing has become an appealing choice for health research. Numerous studies over the years have demonstrated the promise of using smartphone‐based sensing to monitor a range of health conditions, particularly mental health conditions. However, as research is progressing to develop the predictive capabilities of smartphones, it becomes even more crucial to fully understand the capabilities and limitations of using this technology, given its potential impact on human health. To this end, this paper presents a narrative review of smartphone-sensing literature from the past 5 years, to highlight the opportunities and challenges of this approach in healthcare. It provides an overview of the type of health conditions studied, the types of data collected, tools used, and the challenges encountered in using smartphones for healthcare studies, which aims to serve as a guide for researchers wishing to embark on similar research in the future. Our findings highlight the predominance of mental health studies, discuss the opportunities of using standardized sensing approaches and machine‐learning advancements, and present the trends of smartphone sensing in healthcare over the years.
KW - digital health
KW - e‐health
KW - narrative review
KW - smartphone sensing
UR - http://www.scopus.com/inward/record.url?scp=85130281542&partnerID=8YFLogxK
U2 - 10.3390/s22103893
DO - 10.3390/s22103893
M3 - Review Article
C2 - 35632301
AN - SCOPUS:85130281542
SN - 1424-8220
VL - 22
JO - Sensors
JF - Sensors
IS - 10
M1 - 3893
ER -