Design and Study of a Smart Cup for Monitoring the Arm and Hand Activity of Stroke Patients

Towards an AI-driven soft toy for automatically detecting and classifying infant-toy interactions using optical force sensors

Introduction: It is crucial to identify neurodevelopmental disorders in infants early on for timely intervention to improve their long-term outcomes. Combining natural play with quantitative measurements of developmental milestones can be an effective way to swiftly and efficiently detect infants who are at risk of neurodevelopmental delays. Clinical studies have established differences in toy interaction behaviors between full-term infants and pre-term infants who are at risk for cerebral palsy and other developmental disorders. Methods: The proposed toy aims to improve the quantitative assessment of infant-toy interactions and fully automate the process of detecting those infants at risk of developing motor delays. This paper describes the design and development of a toy that uniquely utilizes a collection of soft lossy force sensors which are developed using optical fibers to gather play interaction data from infants laying supine in a gym. An example interaction database was created by having 15 adults complete a total of 2480 interactions with the toy consisting of 620 touches, 620 punches-"kick substitute," 620 weak grasps and 620 strong grasps. Results: The data is analyzed for patterns of interaction with the toy face using a machine learning model developed to classify the four interactions present in the database. Results indicate that the configuration of 6 soft force sensors on the face created unique activation patterns. Discussion: The machine learning algorithm was able to identify the distinct action types from the data, suggesting the potential usability of the toy. Next steps involve sensorizing the entire toy and testing with infants.

Characteristics and Applications of Technology-Aided Hand Functional Assessment: A Systematic Review

Technology-aided hand functional assessment has received considerable attention in recent years. Its applications are required to obtain objective, reliable, and sensitive methods for clinical decision making. This systematic review aims to investigate and discuss characteristics of technology-aided hand functional assessment and their applications, in terms of the adopted sensing technology, evaluation methods and purposes. Based on the shortcomings of current applications, and opportunities offered by emerging systems, this review aims to support the design and the translation to clinical practice of technology-aided hand functional assessment. To this end, a systematic literature search was led, according to recommended PRISMA guidelines, in PubMed and IEEE Xplore databases. The search yielded 208 records, resulting into 23 articles included in the study. Glove-based systems, instrumented objects and body-networked sensor systems appeared from the search, together with vision-based motion capture systems, end-effector, and exoskeleton systems. Inertial measurement unit (IMU) and force sensing resistor (FSR) resulted the sensing technologies most used for kinematic and kinetic analysis. A lack of standardization in system metrics and assessment methods emerged. Future studies that pertinently discuss the pathophysiological content and clinimetrics properties of new systems are required for leading technologies to clinical acceptance.

Determining Factors that Influence Adoption of New Post-Stroke Sensorimotor Rehabilitation Devices in the USA

Rehabilitation device efficacy alone does not lead to clinical practice adoption. Previous literature identifies drivers for device adoption by therapists but does not identify the best settings to introduce devices, the roles of different stakeholders including rehabilitation directors, or specific criteria to be met during device development. The objective of this work was to provide insights into these areas to increase clinical adoption of post-stroke restorative rehabilitation devices. We interviewed 107 persons including physical/occupational therapists, rehabilitation directors, and stroke survivors and performed content analysis. Unique to this work, care settings in which therapy goals are best aligned for restorative devices were found to be outpatient rehabilitation, followed by inpatient rehabilitation. Therapists are the major influencers for adoption because they typically introduce new rehabilitation devices to patients for both clinic and home use. We also learned therapists' utilization rate of a rehabilitation device influences a rehabilitation director's decision to acquire the device for facility use. Main drivers for each stakeholder are identified, along with specific criteria to add details to findings from previous literature. In addition, drivers for home adoption of rehabilitation devices by patients are identified. Rehabilitation device development should consider the best settings to first introduce the device, roles of each stakeholder, and drivers that influence each stakeholder, to accelerate successful adoption of the developed device.

IoT Services and Applications in Rehabilitation: An Interdisciplinary and Meta-Analysis Review

Internet of things (IoT) is a designation given to a technological system that can enhance possibilities of connectivity between people and things and has been showing to be an opportunity for developing and improving smart rehabilitation systems and helps in the e-Health area.

OBJECTIVE

to identify works involving IoT that deal with the development, architecture, application, implementation, use of technological equipment in the area of patient rehabilitation. Technology or Method: A systematic review based on Kitchenham's suggestions combined to the PRISMA protocol. The search strategy was carried out comprehensively in the IEEE Xplore Digital Library, Web of Science and Scopus databases with the data extraction method for assessment and analysis consist only of primary studies articles related to the IoT and Rehabilitation of patients.

RESULTS

We found 29 studies that addressed the research question, and all were classified based on scientific evidence.

CONCLUSIONS

This systematic review presents the current state of the art on the IoT in health rehabilitation and identifies findings in interdisciplinary researches in different clinical cases with technological systems including wearable devices and cloud computing. The gaps in IoT for rehabilitation include the need for more clinical randomized controlled trials and longitudinal studies. Clinical Impact: This paper has an interdisciplinary feature and includes areas such as Internet of Things Information and Communication Technology with their application to the medical and rehabilitation domains.

Design and implementation of an intelligent monitoring system for household added salt consumption in China based on a real-world study: a randomized controlled trial

BACKGROUND

A high intake of salt is a major risk factor for cardiovascular diseases. Despite decades of effort to reduce salt consumption, the salt intake in China is still considerably above the recommended level. Thus, this study aims to design and implement an intelligent household added salt monitoring system (SALTCHECKER) to monitor and control added salt consumption in Chinese households.

METHODS

A randomized controlled trial will be conducted among households to test the effect of a SALTCHECKER in Chongqing, China. The test modalities are the SALTCHECKER (with a smart salt checker and a salt-limiting WeChat mini programme) compared to a salt checker (with only a weighing function). The effectiveness of the system will be investigated by assessing the daily added salt intake of each household member and the salt consumption-related knowledge, attitude and practice (KAP) of the household's main cook. Assessments will be performed at baseline and at 3 and 6 months.

DISCUSSION

This study will be the first to explore the effect of the household added salt monitoring system on the reduction in salt intake in households. If the intelligent monitoring system is found to be effective in limiting household added salt consumption, it could provide scientific evidence on reducing salt consumption and preventing salt-related chronic diseases.

TRIAL REGISTRATION

Chinese clinical trial registry (Primary registry in the World Health Organization registry network): ChiCTR1800018586. Date of registration: September 25, 2018.

Internet of things in medicine: A systematic mapping study

CONTEXT

The current studies on IoT in healthcare have reviewed the uses of this technology in a combination of healthcare domains, including nursing, rehabilitation sciences, ambient assisted living (AAL), medicine, etc. However, no review study has scrutinized IoT advances exclusively in medicine irrespective of other healthcare domains.

OBJECTIVES

The purpose of the current study was to identify and map the current IoT developments in medicine through providing graphical/tabular classifications on the current experimental and practical IoT information in medicine, the involved medical sub-fields, the locations of IoT use in medicine, and the bibliometric information about IoT research articles.

METHODS

In this systematic mapping study, the studies published between 2000 and 2018 in major online scientific databases, including IEEE Xplore, Web of Science, Scopus, and PubMed were screened. A total of 3679 papers were found from which 89 papers were finally selected based on specific inclusion/exclusion criteria.

RESULTS

While the majority of medical IoT studies were experimental and prototyping in nature, they generally reported that home was the most popular place for medical IoT applications. It was also found that neurology, cardiology, and psychiatry/psychology were the medical sub-fields receiving the most IoT attention. Bibliometric analysis showed that IEEE Internet of Things Journal has published the most influential IoT articles. India, China and the United States were found to be the most involved countries in medical IoT research.

CONCLUSIONS

Although IoT has not yet been employed in some medical sub-fields, recent substantial surge in the number of medical IoT studies will most likely lead to the engagement of more medical sub-fields in the years to come. IoT literature also shows that the ambiguity of assigning a variety of terms to IoT, namely system, platform, device, tool, etc., and the interchangeable uses of these terms require a taxonomy study to investigate the precise definition of these terms. Other areas of research have also been mentioned at the end of this article.