Digitized
telemedicine tools with the Internet of Things (IoT)
started advancing into our daily lives and have been incorporated
with commercial wearable gadgets for noninvasive remote health monitoring.
The newly established tools have been steered toward a new era of
decentralized healthcare. The advancement of a telemedicine wearable
monitoring system has attracted enormous interest in the multimodal
big data acquisition of real-time physiological and biochemical information
via noninvasive methods for any health-related industries. The expectation
of telemedicine wearable creation has been focused on early diagnosis
of multiple diseases and minimizing the cost of high-tech and invasive
treatments. However, only limited progress has been directed toward
the development of telemedicine wearable sensors. This Perspective
addresses the advancement of these wearable sensors that encounter
multiple challenges on the forefront and technological gaps hampering
the realization of health monitoring at molecular levels related to
smart materials mostly limited to single use, issues of selectivity
to analytes, low sensitivity to targets, miniaturization, and lack
of artificial intelligence to perform multiple tasks and secure big
data transfer. Sensor stability with minimized signal drift, on-body
sensor reusability, and long-term continuous health monitoring provides
key analytical challenges. This Perspective also focuses on, promotes,
and highlights wearable sensors with a distinct capability to interconnect
with telemedicine healthcare for physical sensing and multiplex sensing
at deeper levels. Moreover, it points out some critical challenges
in different material aspects and promotes what it will take to advance
the current state-of-art wearable sensors for telemedicine healthcare.
Ultimately, this Perspective is to draw attention to some potential
blind spots of wearable technology development and to inspire further
development of this integrated technology in mitigating multimorbidity
in aging societies through health monitoring at molecular levels to
identify signs of diseases.