Recognition of Activities of Daily Living in natural &amp;#x201C;at home&amp;#x201D; scenario for assessment of Alzheimer's disease patients

Buso, Vincent; Hopper, Louise; Benois-Pineau, Jenny; Plans, Pierre-Marie; Megret, Rémi

doi:10.1109/icmew.2015.7169861

Cited by 6 publications

(6 citation statements)

References 17 publications

(19 reference statements)

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“…A commonly employed solution to obtain a reference for gait detection and activity discrimination is the use of body-worn cameras pointing to the subjects feet ( Buso et al, 2015 ; Full et al, 2015 ; Hickey et al, 2016 ). However, besides potential privacy issues, the temporal resolution of this approach depends on camera frame rate.…”

Section: Introductionmentioning

confidence: 99%

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

Salis,

Bertuletti,

Bonci

et al. 2023

Front. Bioeng. Biotechnol.

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Introduction: Accurately assessing people’s gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors).Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity.Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72–4.87 steps/min, stride length 0.04–0.06 m, walking speed 0.03–0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

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Section: Introductionmentioning

confidence: 99%

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

Salis,

Bertuletti,

Bonci

et al. 2023

Front. Bioeng. Biotechnol.

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“…The various kinds of daily activities should be able to be monitored and recognized to know the cognitive situation of the elderly people in order that the MCI could be detected at the beginning. Vincent et al proposed a system which could recognize 8 kinds of activities for the people with the cognitive impairment [33]. The activities were such as feeding birds, preparing and eating meal, making tea, playing a CD and so on.…”

Section: Detecting the Cognitive Impairment By Recognizing Activitiesmentioning

confidence: 99%

A Survey of the State-of-the-Art Techniques for Cognitive Impairment Detection in the Elderly

Fei

Yang

et al. 2017

Communications in Computer and Information Science

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With a growing number of elderly people in the UK, more and more of them suffer from various kinds of cognitive impairment. Cognitive impairment can be divided into different stages such as mild cognitive impairment (MCI) and severe cognitive impairment like dementia. Its early detection can be of great importance. However, it is challenging to detect cognitive impairment in the early stage with high accuracy and low cost, when most of the symptoms may not be fully expressed. This survey paper mainly reviews the state of the art techniques for the early detection of cognitive impairment and compares their advantages and weaknesses. In order to build an effective and low-cost automatic system for detecting and monitoring the cognitive impairment for a wide range of elderly people, the applications of computer vision techniques for the early detection of cognitive impairment by monitoring facial expressions, body movements and eye movements are highlighted in this paper. In additional to technique review, the main research challenges for the early detection of cognitive impairment with high accuracy and low cost are analysed in depth. Through carefully comparing and contrasting the currently popular techniques for their advantages and weaknesses, some important research directions are particularly pointed out and highlighted from the viewpoints of the authors alone.

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“…A commonly employed solution to obtain a reference for gait detection and activity discrimination is the use of body-worn cameras pointing to the subjects' feet (Full et al 2015;Buso et al 2015;Hickey et al 2017). However, besides potential privacy issues, the temporal resolution of this approach depends on camera frame rate.…”

Section: Introductionmentioning

confidence: 99%

A multi-sensor wearable system for gait assessment in real-world conditions: performance in individuals with impaired mobility

Salis¹,

Bertuletti²,

Bonci³

et al. 2023

Preprint

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Accurately assessing people’s gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (SDA, including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-hours of real-world unsupervised activity. Excellent absolute agreement (ICC > 0.95) and very limited mean absolute errors were observed for all cohorts and DMOs (cadence ≤ 0.61 steps/min, stride length ≤ 0.02 m, walking speed ≤ 0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the SDA (cadence 2.72–4.87 steps/min, stride length 0.04–0.06 m, walking speed 0.03–0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-hours acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

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Recognition of Activities of Daily Living in natural “at home” scenario for assessment of Alzheimer's disease patients

Cited by 6 publications

References 17 publications

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

A Survey of the State-of-the-Art Techniques for Cognitive Impairment Detection in the Elderly

A multi-sensor wearable system for gait assessment in real-world conditions: performance in individuals with impaired mobility

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