The Science of Body Literacy: How Wearables Are Changing Women’s Health
Author: Shaghayegh Moghimikandelousi, PhD Candidate in Biomedical Engineering, McMaster University | Editors: Romina Garcia de leon and Tashi Stampp (blog coordinators)
Published: August 21st, 2026
What exactly is a wearable device and how can it support women’s health?
To understand wearable devices in women’s health, it’s important to understand that there has been a fundamental limitation in women’s health monitoring that has persisted across different eras. Generally, women go to the clinic, measurements are taken and decisions are made based on a snapshot. However, the physiology of the female body is not static and there are changes at different timepoints. Hormones fluctuate at different stages such as puberty, pregnancy, and menopause. The problem is we are sampling a dynamic system as if it were static. One promising solution is biomonitoring which is the capturing of time-dependent physiological changes and data in this context.
To achieve this goal, wearable devices have been introduced.They integrate multiple sensing approaches to monitor both physical parameters, such as basal body temperature, heart rate, vaginal temperature, and uterine contractions, and chemical biomarkers, including hormones, glucose, and indicators of bacterial infection detected through sialidase- or DNA-based sensing methods. These sensors can be worn, attached or be close to the body to collect data over time such as smart textiles (e.g. bra, underwear and other clothing), smart watches, skin patches, devices that track walking and movement patterns, and small vaginal devices that continuously monitor parameters such as temperature.
Common methods that are frequently used in wearable sensors are electrochemical biosensors which detect the analyte, by measuring small electrical changes produced when that substance undergoes a chemical reaction at the sensor surface. An example of this is continuous glucose monitoring that is very common for monitoring diabetes (such as gestational diabetes). Another important shift is moving away from blood as the only source of sampling. Wearable sensors are using alternative fluid including sweat, vaginal discharge and interstitial fluid as anon-invasive sampling method.
What does it really mean to build ‘body literacy’? How do these devices help a woman understand when something is actually wrong versus when her body is just doing what it’s supposed to do?
One of the most important roles of wearable sensors is collecting the data over time which creates a pattern for individuals. Moreover, instead of comparing these health data to the population average, it allows one to build a personal baseline over time. So, in this context, building body literacy means helping women understand how their body functions or how their pattern changes. Especially for women’s health, recognizing menstrual-cycle patterns, changes in vaginal pH or discharge, fertility signals, pregnancy-related changes, hormone fluctuations, sleep, heart rate, temperature, and other measurable indicators are all very crucial. One of the common examples will be the correlation of body temperature and ovulation. Before ovulation estrogens rise resulting in the lowering of body temperature. After ovulation, due to the increase of progesterone, the body temperature will rise around 0.5-0.80C. Monitoring body temperature can help women monitor their ovulation. Another example of emerging technologies are using the smart bras, textile-based antennas, and ultrasound patches which can help women track and understand normal breast tissue change and identify unusual patterns. These wearables can detect tissue change by monitoring the stiffness or density of breast tissue over time. Although these devices are not intended to be a replacement for clinical methods such as getting, they will increase the awareness of body change and encourage the earlier medical assessment.
How effective are commercially-available wearables at monitoring women’s health variables?
There are multiple wearable devices in the markets for breast tissue monitoring (e.g. iBreastExam®, Invenia ABUS 2.0, and SmartBra EZ Rose® ); temperature for fertility (e.g. Ava Bracelet, OvuFirst, OvulaRing, TempDrop™, and femSense); biometrics for pregnancy (e.g. Nuvo, and Bloomlife Connects); motion,gait pattern, and bone mineral density mainly for osteoporosis (e.g. Muvone, ActiGraph wGT3X-BT®, MoveMonitor, and OsteoBoost). While commercially available wearables are effective for the continuous tracking of these variables, their effectiveness is dependent on the location and time of use. For example, daily activity will affect wrist-based temperature readings and make them more reliable at night when the body is at rest. An alternative option is the vaginal lodger which provides a more stable temperature reading because it is less affected by the daily activity and environmental condition. As mentioned above, commercially available wearables are intended to support health monitoring rather than serve as alternatives to, or replacements for, professional medical assessment.
What are some of the biggest problems with the data we currently collect from wearables, and how can we make sure these devices are actually accurate and helpful for all women?
One of the main challenges for wearable devices is the data collection which will be affected by the device placement, movement and even individuals. Many emerging wearable and mobile-health systems use AI or machine-learning algorithms to interpret data and provide feedback. However, vast amounts of these AI algorithms are developed using biased datasets that do not adequately represent women of different ages, ethnicities, socioeconomic backgrounds, or gender identities. To make these technologies more accurate and useful to the diverse population of women, all of the AI algorithms should be trained on a more diverse dataset and therefore create more clinically relevant algorithms. After that the error rates and limitations should be reported clearly and be designed with accessible interfaces and professional guidance for interpreting the results.
How useful is this data for clinicians, and how can these technologies be integrated into professional care?
Data collected from wearable devices are very useful for the clinicians by providing continuous information rather than just single measurement. It can help by showing trends and even treatment responses or any further changes that seek medical attention. They are more effective when they are integrated into a mobile health (mHealth) App or telemedicine that allows clinicians and professionals to review that data.
