AI Health Archives - Healthentia https://healthentia.com/tag/ai-health/ Tue, 05 Aug 2025 10:47:59 +0000 en-US hourly 1 https://healthentia.com/wp-content/uploads/2020/04/cropped-favicon_512-32x32.png AI Health Archives - Healthentia https://healthentia.com/tag/ai-health/ 32 32 193384636 Enhancing HIV Patient Care through Healthentia https://healthentia.com/enhancing-hiv-patient-care-through-healthentia/ Tue, 19 Mar 2024 14:48:57 +0000 https://healthentia.com/?p=20343 CATEGORY: eHealth, Health monitoring, telemonitoring, COPD Remote patient monitoring SOURCE: Int. J. Environ. Res. Public Health 2020, 17(21), 7893; https://doi.org/10.3390/ijerph17217893 Acceptance and Potential Impact of the eWALL Platform for Health Monitoring and Promotion in Persons with a Chronic Disease or Age-Related Impairment Francesco Infarinato, Stephanie Jansen-Kosterink, Paola Romano, Lex van Velsen, Harm op den Akker, Federica Rizza, Marco Ottaviani, Sofoklis Kyriazakos, Beatrix Wais-Zechmann, Markus Garschall, Stefano Bonassi,...

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CATEGORY: eHealth, Health monitoring, telemonitoring, COPD Remote patient monitoring

SOURCE: Int. J. Environ. Res. Public Health 2020, 17(21), 7893; https://doi.org/10.3390/ijerph17217893

Acceptance and Potential Impact of the eWALL Platform for Health Monitoring and Promotion in Persons with a Chronic Disease or Age-Related Impairment

Francesco Infarinato, Stephanie Jansen-Kosterink, Paola Romano, Lex van Velsen, Harm op den Akker, Federica Rizza, Marco Ottaviani, Sofoklis Kyriazakos, Beatrix Wais-Zechmann, Markus Garschall, Stefano Bonassi, and Hermie J. Hermens

Abstract

Pervasive health technologies can increase the effectiveness of personal health monitoring and training, but more user studies are necessary to understand the interest for these technologies, and how they should be designed and implemented. In the present study, we evaluated eWALL, a user-centered pervasive health technology consisting of a platform that monitors users' physical and cognitive behavior, providing feedback and motivation via an easy-to-use, touch-based user interface. The eWALL was placed for one month in the home of 48 subjects with a chronic condition (chronic obstructive pulmonary disease-COPD or mild cognitive impairment-MCI) or with an age-related impairment. User acceptance, platform use, and potential clinical effects were evaluated using surveys, data logs, and clinical scales. Although some features of the platform need to be improved before reaching technical maturity and making a difference in patients' lives, the real-life evaluation of eWALL has shown how some features may influence patients' intention to use this promising technology. Furthermore, this study made it clear how the free use of different health apps is modulated by the real needs of the patient and by their usefulness in the context of the patient's clinical status.

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]]> 20343 Optimizing Insulin Dosing for Type 2 Diabetes with AI Assistant https://healthentia.com/optimizing-insulin-dosing-for-type-2-diabetes-with-ai-assistant/ Wed, 17 Jan 2024 12:44:06 +0000 https://healthentia.com/?p=20274   Managing insulin therapy for type 2 diabetes can be challenging due to the need for frequent dose adjustments. This study examined whether a voice-based AI assistant could help patients achieve better blood sugar control by adjusting their insulin dosages more effectively. In an RCT presented by Ashwin Nayak et al in JAMA Netw Open. 2023;6(12):...

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Managing insulin therapy for type 2 diabetes can be challenging due to the need for frequent dose adjustments. This study examined whether a voice-based AI assistant could help patients achieve better blood sugar control by adjusting their insulin dosages more effectively.

In an RCT presented by Ashwin Nayak et al in JAMA Netw Open. 2023;6(12): e2340232, titled Use of Voice-Based Conversational Artificial Intelligence for Basal Insulin Prescription Management Among Patients With Type 2 Diabetes, is presented the effectiveness of voice-based conversational AI applications in facilitating swift optimization of basal insulin dosage for individuals with type 2 diabetes.

The study involved 32 adults with type 2 diabetes who either used the AI assistant or received standard care. Those who used the AI assistant reached the optimal insulin dose significantly faster (median of 15 days vs. over 56 days for standard care). Additionally, AI users had better insulin adherence (83% vs. 50% for standard care), improved glycemic control, and reduced diabetes-related emotional distress.

These findings suggest that voice-based AI assistants can be a valuable tool for type 2 diabetes patients, helping them achieve better blood sugar control and improve their overall well-being. By providing personalized and adaptive insulin dosing recommendations, voice-based AI assistants can empower patients to take control of their condition and achieve better health outcomes.

The ability to quickly reach the optimal insulin dose, enhance adherence, and reduce emotional distress highlights the transformative impact of this technology in improving the lives of individuals with type 2 diabetes.

As AI continues to advance, its role in healthcare is expected to expand significantly. Voice-based AI assistants like the one used in this study offer a promising approach to medication titration and personalized treatment guidance, holding the potential to revolutionize chronic disease management and improve patient outcomes.

Explore the VirT2D study for detailed insights into how Healthentia provides personalized coaching for individuals with type 2 diabetes, aiming to enhance patient care in diabetes management.

 

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