Mobile Test of Manual Dexterity in the Diagnostics of Frail Geriatric Patients – Pilot Study

Seiffert, Piotr; Kawa, Jacek; Marcisz, C; Stępień, Paula; Czernek, Małgorzata; Bugdoł, Marcin; Kapko, Wojciech; Derejczyk, Jarosław

doi:10.1007/978-3-030-15472-1_6

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…Additionally, in some studies, the concept of frailty was used in the context of other clinical conditions such as cancer or dementia. This is consistent with the findings from previous review papers 45,46 where the term frailty was loosely based on different concepts and tools, or simply assigned to old participants without mentioning a frailty assessment. We found great heterogeneity in reporting and choosing a frailty score and in the nature of the frailty assessment.…”

Section: Discussionsupporting

confidence: 91%

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Digital Health Interventions among People Living with Frailty: A Scoping Review

Linn

Goetzinger

Regnaux

et al. 2021

Journal of the American Medical Directors Association

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Objectives: Digital health interventions (DHIs) are interesting resources to improve various health conditions. However, their use in the older and frail population is still sparse. We aimed to give an overview of DHI used in the frail older population. Design: Scoping review with PRISMA guidelines based on Population, Concept, and Context. Setting and participants: We included original studies in English with DHI (concept) on people described as frail (population) in the clinical or community setting (context) and no limitation on date of publication. We searched 3 online databases (PubMed, Scopus, and Web of Science). Measures: We described DHI in terms of purpose, delivering, content and assessment. We also described frailty assessment and study design. Results: We included 105 studies that fulfilled our eligibility criteria. The most frequently reported DHIs were with the purpose of monitoring (45; 43%), with a delivery method of sensor-based technologies (59; 56%), with a content of feedback to users (34; 32%), and for assessment of feasibility (57; 54%). Efficacy was reported in 31 (30%) studies and usability/feasibility in 57 (55%) studies. The most common study design was descriptive exploratory for new methodology or technology (24; 23%). There were 14 (13%) randomized controlled trials, with only 4 of 14 studies (29%) showing a low or moderate risk of bias. Frailty assessment using validated scales was reported in only 47 (45%) studies. Conclusions and Implications: There was much heterogeneity among frailty assessments, study designs, and evaluations of DHIs. There is now a strong need for more standardized approaches to assess frailty, well-structured randomized controlled trials, and proper evaluation and report. This work will contribute to the development of better DHIs in this vulnerable population.

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Section: Discussionsupporting

confidence: 91%

“…44 Liu et al 45 published a systematic review on the readiness of the older population for smart home technologies. Rialle et al 46 reviewed recent health "smart" home projects and concepts. Karlsen et al 47 performed a qualitative review on telecare at home for community-dwelling older people.…”

Section: Discussionmentioning

confidence: 99%

Digital Health Interventions among People Living with Frailty: A Scoping Review

Linn

Goetzinger

Regnaux

et al. 2021

Journal of the American Medical Directors Association

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“…Across studies, motion data from the sensors identified showed an average Pearson r clinical validity coefficient of 0.52 (Figure 4 [27,28,31,[35][36][37][38][39][40][41]44,47,48,[50][51][52][53]57,58,[66][67][68][69][70][71][72][73][74]76,77,[80][81][82][83][84]86,91,92,[95][96][97][98][99]101,102,104,106,[108][109][110]112,…”

Section: Analytical and Clinical Validationmentioning

confidence: 99%

Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review

et al. 2022

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Background With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes. Objective We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations. Methods A systematic literature review was conducted by searching Embase, MEDLINE, CENTRAL (January 1, 2015, to June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. Results A total of 91 publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson disease (n=51 studies), followed by stroke (n=5), Huntington disease (n=5), and multiple sclerosis (n=2). A total of 42 motion-detecting devices were identified, and the majority (n=27, 64%) were created for the purpose of health care–related data collection, although approximately 25% were personal electronic devices (eg, smartphones and watches) and 11% were entertainment consoles (eg, Microsoft Kinect or Xbox and Nintendo Wii). The primary motion outcomes were related to gait (n=30), gross motor movements (n=25), and fine motor movements (n=23). As a group, sensor-derived motion data showed a mean sensitivity of 0.83 (SD 7.27), a mean specificity of 0.84 (SD 15.40), a mean accuracy of 0.90 (SD 5.87) in discriminating between diseased individuals and healthy controls, and a mean Pearson r validity coefficient of 0.52 (SD 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-laboratory and at-home sensor-based assessments nor between device class (ie, health care–related device, personal electronic devices, and entertainment consoles). Conclusions Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of the recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than one-quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.

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Digital Devices for Assessing Motor Functions in Mobility Impaired and Healthy Populations: A Systematic Literature Review (Preprint)

Guo¹,

Chiesa²,

Moor³

et al. 2022

Preprint

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BACKGROUND With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes. OBJECTIVE We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults, and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations. METHODS A systematic literature review was conducted by searching Embase, MEDLINE®, CENTRAL (January 1, 2015 – June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by two independent reviewers. RESULTS Ninety-one publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson’s disease (k = 51 studies), followed by stroke (k = 5), Huntington’s disease (k = 5), and multiple sclerosis (k = 2). A total of 42 motion-detecting devices were identified, and the majority (k = 27; 64%) were created for the purpose of healthcare-related data collection, though approximately 25% were personal electronic devices (e.g., smartphones, watches) and 11% were entertainment consoles (e.g., Microsoft Kinect/Xbox™, Nintendo Wii™). The primary motion outcomes were related to gait (k = 30), gross motor movements (k = 25), and fine motor movements (k = 23). As a group, sensor-derived motion data showed a mean sensitivity of .83 (SD = 7.27), mean specificity of .84 (SD = 15.40), mean accuracy of .90 (SD = 5.87) in discriminating between diseased individuals and healthy controls, and mean Pearson’s r validity coefficient of .52 (SD = 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-lab and at-home sensor-based assessments, nor between device class (i.e., healthcare-related device, personal electronic devices, entertainment consoles). CONCLUSIONS Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than a quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.

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Mobile Test of Manual Dexterity in the Diagnostics of Frail Geriatric Patients – Pilot Study

Cited by 3 publications

References 15 publications

Digital Health Interventions among People Living with Frailty: A Scoping Review

Digital Health Interventions among People Living with Frailty: A Scoping Review

Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review

Digital Devices for Assessing Motor Functions in Mobility Impaired and Healthy Populations: A Systematic Literature Review (Preprint)

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