A fabric-based wearable sensor for continuous monitoring of decubitus ulcer of subjects lying on a bed

For multifunctional wearable sensing systems, problems related to wireless and continuous communication and soft, noninvasive, and disposable functionality issues should be solved for precise physiological signal detection. To measure the critical transitions of pressure, temperature, and skin impedance when continuous pressure is applied on skin and tissue, we developed a sensor for decubitus ulcers using conventional analog circuitry for wireless and continuous communication in a disposable, breathable fabric-based multifunctional sensing system capable of conformal contact. By integrating the designed wireless communication module into a multifunctional sensor, we obtained sensing data that were sent sequentially and continuously to a customized mobile phone app. With a small-sized and lightweight module, our sensing system operated over 24 h with a coin-cell battery consuming minimum energy for intermittent sensing and transmission. We conducted a pilot test on healthy subjects to evaluate the adequate wireless operation of the multifunctional sensing system when applied to the body. By solving the aforementioned practical problems, including those related to wireless and continuous communication and soft, noninvasive, and disposable functionality issues, our fabric-based multifunctional decubitus ulcer sensor successfully measured applied pressure, skin temperature, and electrical skin impedance.

A fabric-based multifunctional sensor for the early detection of skin decubitus ulcers

Monitoring biosignals at the skin interface is necessary to suppress the potential for decubitus ulcers in immobile patients confined to bed. We develop conformally contacted, disposable, and breathable fabric-based electronic devices to detect skin impedance, applied pressure, and temperature, simultaneously. Based on the experimental evaluation of the multifunctional sensors, a combination of robust AgNW electrodes, soft ionogel capacitive pressure sensor, and resistive temperature sensor on fabric provides alarmed the initiation of early-stage decubitus ulcers without signal distortion under the external stimulus. For clinical verification, an animal model is established with a pair of magnets to mimic a human decubitus ulcers model in murine in vivo. The evidence of pressure-induced ischemic injury is confirmed with the naked eye and histological and molecular biomarker analyses. Our multifunctional integrated sensor detects the critical time for early-stage decubitus ulcer, establishing a robust correlation with the biophysical parameters of skin ischemia and integrity, including temperature and impedance.

Validation of a gyroscope-based wearable device for real-time position monitoring of patients in a hospital

BACKGROUND

Monitoring patients' position is important, but there have been few studies related to validation.

OBJECTIVE

The objective of this study was to assess the validity of position monitoring measured using a wearable device by comparing the device's measurements to a patient's actual position.

METHODS

We constructed a wearable device with a three-axis gyroscope and applied it to 10 patients who were unable to change their position independently. We compared the actual angle of the position and the angle transmitted from the wearable device using a Bland-Altman plot and a receiver operating characteristic curve.

RESULTS

We compared the actual angle of the position and the angle transmitted from the wearable device using a Bland-Altman plot, but it was difficult to observe statistical similarity. The angles transmitted from the wearable device in the lateral and supine positions showed significant differences. The cutoff value separating the lateral and supine positions was found to be 27.1∘ (sensitivity = 100%, specificity = 99.9%).

CONCLUSIONS

Through our method, the measured values from the gyroscope-based wearable device did not accurately reflect the patient's actual position. However, the wearable device was able to distinguish the lateral position from the supine position.

A deep learning approach for pressure ulcer prevention using wearable computing

In recent years, statistics have confirmed that the number of elderly people is increasing. Aging always has a strong impact on the health of a human being; from a biological of point view, this process usually leads to several types of diseases mainly due to the impairment of the organism. In such a context, healthcare plays an important role in the healing process, trying to address these problems. One of the consequences of aging is the formation of pressure ulcers (PUs), which have a negative impact on the life quality of patients in the hospital, not only from a healthiness perspective but also psychologically. In this sense, e-health proposes several approaches to deal with this problem, however, these are not always very accurate and capable to prevent issues of this kind efficiently. Moreover, the proposed solutions are usually expensive and invasive. In this paper we were able to collect data coming from inertial sensors with the aim, in line with the Human-centric Computing (HC) paradigm, to design and implement a non-invasive system of wearable sensors for the prevention of PUs through deep learning techniques. In particular, using inertial sensors we are able to estimate the positions of the patients, and send an alert signal when he/she remains in the same position for too long a period of time. To train our system we built a dataset by monitoring the positions of a set of patients during their period of hospitalization, and we show here the results, demonstrating the feasibility of this technique and the level of accuracy we were able to reach, comparing our model with other popular machine learning approaches.