Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review
<p>PRISMA diagram: this figure represents the flow of study selection through identification, screening, eligibility and inclusion.</p> "> Figure 2
<p>Spatiotemporal parameters most frequently evaluated in selected articles.</p> "> Figure 3
<p>Smartphone placement: the corresponding position of the smartphone reported.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Identifying the Research Question
2.2. Literature Search Methodology
3. Results
Data Analyses
4. Discussion
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Reference | Experimental Group (N, Mean Age SD, Sex) | Patients with History of Falls | Mobile Phone App Used | Smartphone Used and Placement | Spatiotemporal Parameters Investigated | Main Findings |
---|---|---|---|---|---|---|
Zhong et al., 2020 [20] | 148 participants (40 M/108 F) Age: 69.8 (7.0) | Yes. N = 37 | Pocket Gait | Android smartphone (vivo Z1, Android operating system version 8.1, VIVO Technology Co, Dongguan, China) with a sacroiliac belt | Step symmetry, step frequency, RMS, step regularity and step variability | The Pocket Gait app is a health management tool that enables older adults to self-manage their gait quality and prevent adverse outcomes. The step frequency of participants in the age group 60 to 69 years was significantly higher than that of participants in the other age groups. |
Shafi et al., 2023 [21] | 83 participants(33 M/50 F) Age: 56.12 ± 6.06 years | Berg Balance Scale = 46 to 54, indicating a mild risk of falls | G&B | iOS. iPhone 7 used with a sacroiliac belt | Gait velocity, gait symmetry (periodicity index) (%), step time variability (%), average step length, average step time, step length variability (%), step length asymmetry (%) and step time asymmetry | The G&B app excels in specific areas, particularly in measuring walking speed, step length and step time, as emphasized by the alignment of these parameters with established clinical benchmarks and their moderate-to-excellent reliability. However, gaps remain, especially concerning the reliable assessment of steadiness, step length variability, step time variability, step length asymmetry and step time asymmetry. |
Doshi et al., 2023 [22] | 49 participants(7 M/42 F) Age: 75.6 (8.3) | Yes. N = 14 | Lockhart Monitor | iOS. Apple smartphone used with a sacroiliac belt | Gait velocity | People with osteoporosis with a history of falls can be differentiated by using dynamic real-time measurements that can be easily captured using a smartphone app. Participants in the non-fall group walked faster (0.96 m/s) than those who had fallen (0.79 m/s). |
Kawai et al., 2023 [23] | 163 participants (104 M/59 F) Age: 72.1 (6.85) | n = 34 frailty group assessed using Kihon checklist score [24]. | Authors customized a daily walking speed measurement app (Chami, InfoDeliver Co. Ltd., Tokyo, Japan) | Android smartphones worn in the pant pocket | Gait velocity, step length, cadence and number of steps | DWS measured using the smartphone application was associated with frailty. Step length was significantly smaller in the frailty group. |
Giannouli et al., 2022 [25] | 57 participants (27 M/30 F) Age: 75.3 (5.9) | Yes. N = 13 | MOBITEC-GP | Android smartphones worn in the pant pocket | Gait velocity | The MOBITEC-GP app showed moderate-to-excellent test–retest reliability and validity of walking speed measurements. |
Olsen et al., 2023 [26] | 34 participants(14 M/20 F) Age: 42–94 | No | G&B app | iOS. iPhone SE used with a sacroiliac belt | Gait velocity, periodicity index, mean step length, mean step time, step length variability, step time variability, step length asymmetry and step time asymmetry | The G&B app offers valid measurements of walking speed, step length and step time with a moderate-to-excellent reliability in older adults. |
Rubin et al., 2022 [27] | 37 participants(5 M/32 F) Age: 71 (69–74) | Yes. N = 8 | Authors customized a Step Test application | iOS. iPhone 8 smartphone was placed in either the patient’s front pants pocket or attached to a waist belt | Cadence | The study demonstrates the feasibility of using gait cadence as a measure to estimate functional capacity. |
Olsen et al., 2024 [28] | 54 participants(20 M/30 F) Age: mean 61.6 | No | G&B app | iOS. iPhone 7 or iPhone SE used with a sacroiliac belt | Gait velocity, mean step length, mean step time, mean left step length, mean right step length, mean left step time, mean right step time, step length variability, step time variability, step time, step length asymmetry and asymmetry | The G&B app has potential to provide valid measurements of step time, step length and walking speed in older adults. |
Zhong et al., 2022 [29] | 100 participants (56 M/44 F) Age: 73.0 (7.7) | Yes. N = 18 | Pocket Gait | Android. Smartphone Huawei Honor v20 used with a sacroiliac belt | Step frequency (Hz), RMS acceleration (m/s2), step time variability, step regularity and step symmetry | The Pocket Gait app could be used to detect early signs of aging; older adults who walked less than 1 km had a lower quality gait compared with their counterparts who walked more than 1 km per day. |
Lee et al., 2024 [14] | 15 participants(15 F) Age: (77.67 ± 6.41) | No | Authors customized a smartphone application | Smartphones worn in the pant pocket | Gait speed | This mobile app has been shown to be valid and reliable for measuring gait speed in older adults and was highly correlated with video-based analysis. |
Pedrero-Sánchez et al., 2023 [30] | 65 participants (M/F: not reported) Age: 68.55 (7.18) | Yes. N = 25 | FallSkip app | Android9. Smartphone Xiaomi Redmi 4 × Model MAG138 used with a sacroiliac belt | AP and ML displacement of the center of mass (CoM) during 30 s standing, vertical and ML excursion of the CoM while walking, average power of turning–sitting movements and standing up, range of AP jerk of CoM during turning–sitting movement and standing up, reaction time and total motion time | Fall risk can be reliably assessed using a simple, fast smartphone protocol that allows accurate fall risk classification among older people and can be a useful screening tool in clinical settings. |
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Brognara, L. Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review. Geriatrics 2024, 9, 95. https://doi.org/10.3390/geriatrics9040095
Brognara L. Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review. Geriatrics. 2024; 9(4):95. https://doi.org/10.3390/geriatrics9040095
Chicago/Turabian StyleBrognara, Lorenzo. 2024. "Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review" Geriatrics 9, no. 4: 95. https://doi.org/10.3390/geriatrics9040095