Health Wearables for Early Detection of Frailty Syndrome in Older Adults in Mexico: An Informed, Structured Process for the Selection of a Suitable Device

Bustamante-Bello, Rogelio; Ruiz-Soto, Gabriela; Ramirez‐Mendoza, Ricardo A.; Avila-Vázquez, Roberto; Montesinos, Luis; Noguez, Julieta; Navarro-Tuch, Sergio A.

doi:10.1016/j.procs.2016.09.057

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…wearable weight, training on use of device) to facilitate user needs rather than ad-hoc selection of technology [29]. Creation of fall and activity recognition systems have shown that older adult involvement is an important process to ensure wearable longevity, where there is a requirement for a 'needs-driven' rather than a 'technology-driven' approach [30][31][32].…”

Section: User Needsmentioning

confidence: 99%

Wearables for independent living in older adults: Gait and falls

Godfrey

2017

Maturitas

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Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) are one approach to offer a viable means for ubiquitous, sustainable and scalable monitoring in habitual free-living environments. Gait has been presented as a relevant (bio) marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of recent wearable gait assessment literature, focusing on the need for an algorithm fusion approach to measurement cumulating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Opportunities for how this domain needs to progress are also summarised. Highlights• Wearables can meet older adults' needs for independent living.• Gait assessment is a (bio)marker within ageing and different pathologies.• Measuring gait with wearables has been innovative but fraught with inconsistencies.

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Section: User Needsmentioning

confidence: 99%

Wearables for independent living in older adults: Gait and falls

Godfrey

2017

Maturitas

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“…It is reported that understanding and quantifying human behaviour and movements are key in the early diagnosis of both mental and physical health problems (Beniczky, Polster et al, 2013;Bustamante-Bello, Ruiz-Soto, Ramírez-Mendoza, 2016;Kim, 2017). However, even though some wearable devices have been developed for early detection of diabetes, Parkinson, breast cancer (Cyrcadia Health ltd., USA), hypoglycemia (HealthPatch from VitalConnect, USA), heart disease (Polar, USA) many of these devices are invasive and relatively expensive.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Computer Vision-Based System to Analyse Behavioral Changes in High School Classrooms

Kim¹,

O’Sullivan

Kolykhalova

et al. 2021

International Journal of Information and Communication Technology Education

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The objectives of this study were to investigate the feasibility of applying computer vision techniques and to analyse changes in behaviour and movement of high school students during class. The study is performed over two phases. Phase one focuses on developing a feasible method to use computer vision-based techniques in high school classes and phase two focuses on the testing of aromatherapy to affect student’s movement. All camera data was processed and analysed by OpenPose, Matlab and EyesWeb. Movement features such as velocity, acceleration, and kinetic energy and postural variables, spinal extension and neck flexion were calculated. Results of phase one, shows significant differences in the overall segment velocity, acceleration, energy, and neck flexion. Similarly, the second phase shows significant differences in velocity, acceleration and jerk for the left shoulder and elbow joints of the group exposed to aroma. In conclusion, the results show the feasibility of using computer vision techniques to apply in a classroom setting.

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