A wearable sensor system for medication adherence prediction

作者：Kalantarian Haik^*; Motamed Babak; Alshurafa Nabil; Sarrafzadeh Majid

来源：Artificial Intelligence in Medicine, 2016, 69: 43-52.

DOI：10.1016/j.artmed.2016.03.004

• Pervasive computing
• Wearable devices
• Medication adherence
• Deglutition
• Piezoelectric sensor

Objective: Studies have revealed that non-adherence to prescribed medication can lead to hospital read-missions, clinical complications, and other negative patient outcomes. Though many techniques have been proposed to improve patient adherence rates, they suffer from low accuracy. Our objective is to develop and test a novel system for assessment of medication adherence.
Methods: Recently, several smart pill bottle technologies have been proposed, which can detect when the bottle has been opened, and even when a pill has been retrieved. However, very few systems can determine if the pill is subsequently ingested or discarded. We propose a system for detecting user adherence to medication using a smart necklace, capable of determining if the medication has been ingested based on the skin movement in the lower part of the neck during a swallow. This, coupled with existing medication adherence systems that detect when medicine is removed from the bottle, can detect a broader range of use-cases with respect to medication adherence.
Results: Using Bayesian networks, we were able to correctly classify between chewable vitamins, saliva swallows, medication capsules, speaking, and drinking water, with average precision and recall of 90.17% and 88.9%, respectively. A total of 135 instances were classified from a total of 20 subjects.
Conclusion: Our experimental evaluations confirm the accuracy of the piezoelectric necklace for detecting medicine swallows and disambiguating them from related actions. Further studies in real-world conditions are necessary to evaluate the efficacy of the proposed scheme.

• 出版日期2016-5
• 单位西北大学