M-HEALTH By PHARMAGEEK

Researchers have figured out a way to use images from a smartphone to identify potentially harmful bacteria on the skin and in the mouth.

A new method that uses smartphone-derived images can identify potentially harmful bacteria on the skin and in the mouth, research shows.

The approach can visually identify microbes on skin contributing to acne and slow wound healing, as well as bacteria in the oral cavity that can cause gingivitis and dental plaques.

Researchers combined a smartphone-case modification with image-processing methods to illuminate bacteria on images taken by a conventional smartphone camera. This approach yielded a relatively low-cost and quick method that could be used at home.

The team augmented a smartphone camera’s capabilities by attaching a small 3D-printed ring containing 10 LED black lights around a smartphone case’s camera opening. The researchers used the LED-augmented smartphone to take images of the oral cavity and skin on the face of two research subjects.

The LED lights ‘excite’ a class of bacteria-derived molecules called porphyrins, causing them to emit a red fluorescent signal that the smartphone camera can then pick up

Other components in the image—such as proteins or oily molecules our bodies produce, as well as skin, teeth, and gums—won’t glow red under LED. They’ll fluoresce in other colors.

The LED illumination gave the team enough visual information to computationally “convert” the RGB colors from the smartphone-derived images into other wavelengths in the visual spectrum. This generates a “pseudo-multispectral” image consisting of 15 different sections of the visual spectrum—rather than the three in the original RGB image.

Obtaining this visual information up front would have required expensive and cumbersome lights, rather than using the relatively inexpensive LED black lights

With their greater degree of visual discrimination, the pseudo-multispectral images clearly resolved porphyrin clusters on the skin and within the oral cavity. In addition, though they tailored this method to show porphyrin, researchers could modify the image-analysis pipeline to detect other bacterial signatures that also fluoresce under LED.

read the study at https://doi.org/10.1016/j.optlaseng.2021.106546

read the original unedited article at https://www.futurity.org/smartphone-images-skin-mouth-bacteria-2581642/

Mobile health apps are becoming increasingly popular, and they provide opportunities for effective health management.

 

Existing chronic disease management (CDM) apps cannot meet users’ practical and urgent needs, and user adhesion is poor. Few studies, however, have investigated the factors that influence the continuance intention of CDM app users.

 

Objective: Starting from the affordances of CDM apps, this study aimed to analyze how such apps can influence continuance intention through the role of health empowerment.

 

Methods: Adopting a stimulus-organism-response framework, an antecedent model was established for continuance intention from the perspective of perceived affordances, uses and gratifications theory, and health empowerment. Perceived affordances were used as the “stimulus,” users’ gratifications and health empowerment were used as the “organism,” and continuance intention was used as the “response.” Data were collected online through a well-known questionnaire survey platform in China, and 323 valid questionnaires were obtained. The theoretical model was tested using structural equation modeling.

 

Results: Perceived connection affordances were found to have significant positive effects on social interactivity gratification (t717=6.201, P<.001) and informativeness gratification (t717=5.068, P<.001).

 

Perceived utilitarian affordances had significant positive effects

• on informativeness gratification (t717=7.029, P<.001),
• technology gratification (t717=8.404, P<.001),
• and function gratification (t717=9.812, P<.001).

 

Perceived hedonic affordances had

• significant positive effects on function gratification (t717=5.305, P<.001)
• and enjoyment gratification (t717=13.768, P<.001).

 

Five gratifications (t717=2.767, P=.005; t717=4.632, P<.001; t717=7.608, P<.001; t717=2.496, P=.012; t717=5.088, P<.001) had significant positive effects on health empowerment.

 

Social interactivity gratification, informativeness gratification, and function gratification had significant positive effects on continuance intention.

 

Technology gratification and enjoyment gratification did not have a significant effect on continuance intention.

 

Health empowerment had a significant positive effect on continuance intention. Health empowerment and gratifications play mediating roles in the influence of affordances on continuance intention.

 

Conclusions: Health empowerment and gratifications of users’ needs are effective ways to promote continuance intention. The gratifications of users’ needs can realize health empowerment and then inspire continuance intention. Affordances are key antecedents that affect gratifications of users’ needs, health empowerment, and continuance intention.

 

The results indicated that users’ perceptions of an app’s affordances can promote the gratification of needs, and the gratification of key needs (ie, social interactivity, informativeness, technology, and function gratification) can stimulate users’ continuance intention. At the same time, the gratification of users’ needs can promote users’ cognitions of health empowerment, thus stimulating continuance intention. Health empowerment was found to play a mediating role in the influence of gratification on continuance intention. From a practical perspective, app service providers should design apps from the perspective of social interaction (eg, providing social networks), utilitarian functions (eg, health self-management), and hedonic functions (eg, enhancing the user’s interest). By meeting users’ various needs, app developers can improve the user’s ability to control his or her own health, thus achieving the purpose of extending the life of the app.

 

more at https://mhealth.jmir.org/2021/5/e21831/

 

 

Lire l'article complet sur : mhealth.jmir.org

The Mayo Clinic has launched a new mHealth platform aimed at helping healthcare providers improve their use of connected health devices in remote patient monitoring and other mobile health programs.

The Remote Diagnostic and Management Platform (RDMP) connects devices to AI resources that would help providers with clinical decisions support and diagnoses in what the Minnesota-based health system calls “event-driven medicine.” It’s designed to help providers in and outside the health system analyze and act on data collected by mHealth devices.

“The dramatically increased use of remote patient telemetry devices coupled with the rapidly accelerating development of AI and machine learning algorithms has the potential to revolutionize diagnostic medicine,With RDMP, clinicians will have access to best-in-class algorithms and care protocols and will be able to serve more patients effectively in remote care settings. The platform will also enable patients to take more control of their health and make better decisions based on insights delivered directly to them.”

read more at https://mhealthintelligence.com/news/mayo-clinic-launches-new-platform-for-analyzing-data-from-mhealth-devices