AgeingUNITS-APANCT05740241
Use of New Tools to Estimate the Intensity of Adapted Physical Activity Sessions
An observational study of Ageing, run by Centre Hospitalier Universitaire de Nice at 1 site in France.
Trial summary
In the field of sport/health, the prescription is generic and individualisation, which is still very rare, is generally linked only to physical performance. These limitations on the implementation of the sessions will result in limiting the effects of the training programme and increasing the risk of injury. Read more about this study
- Who is it for?
- Ages 65 years and olderHealthy volunteers can take part
- Conditions the study is for
- Ageing
- What is being tested?
- Elderly
- How many people
- 87 participants
- Where
- 1 siteFrance
- Study dates
- 5 Feb 2024to 23 Jun 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 years and older
- All sexes
- Healthy volunteers accepted
- Older adult
Study population: healthy volonteers
Who may be able to join
- Person having signed the non-opposition
- Person affiliated to the social security system.
- Male or female adult over 65 years of age.
Who cannot join
- Person under protective measures (guardianship, curators, private, under court protection).
- Person suffering from a neurological problem affecting mobility (MMSE test < 24).
Trial locations and contacts
1 site in 1 country.
About this study
In the field of sport/health, the prescription is generic and individualisation, which is still very rare, is generally linked only to physical performance. These limitations on the implementation of the sessions will result in limiting the effects of the training programme and increasing the risk of injury. It is therefore necessary to develop knowledge and tools to assist physicians and physical activity professionals in their decision making.
The aim of the study is to improve the precision of the calculation of the training load in order to better individualise the management of the participants.
Read the detailed description
Physical activity has been recommended for many years by various health authorities. Indeed, numerous studies have demonstrated the effects of physical activity on the quality of life, the gain of autonomy and the reduction of functional limitations in the elderly. This problem is becoming more and more present with the increase in life expectancy, which increases the prevalence of individuals reaching the status of elderly person. These forecasts suggest that more and more people will have to live with the consequences of age. From this point of view, the management of these people through adapted physical activity is necessary to relieve the health system by limiting the risks of frailty and thus hospitalisation among the elderly. In order to promote adapted physical activity, the role of specialists in this field is to set up physical activity sessions that solicit the neurocognitive, neuromuscular and cardiorespiratory aspects through balance, muscle strengthening and aerobic exercises. These sessions will be defined according to different criteria such as pathology, level of accomplishment of the exercises and the perceived difficulty of the session. For participants, the most common method of quantification is the Borg Rating of Perceived Exertion (RPE) scale. This measure consists of measuring the perception of effort on a scale ranging from 6 for "no perceived effort" to 20 for "maximum effort". The use of this tool has the advantage of having a strong correlation with heart rate at moderate intensities. These different parameters will allow the adapted physical activity engineer to determine a training load according to these different parameters. This training load will then allow the next session(s) to be adjusted to best suit the functional capacities of the participants and thus individualise the treatment of these people. However, this training load is subjective. For professionals in adapted physical activity, the quantification of the training load of the different sessions is based on personal experience. This method is difficult to quantify and generalise to other professionals. Similarly, the feeling of the difficulty of the session is specific to each participant. The quantification of the RPE will be strongly impacted by the last exercises of the session and the group effect. To address this limitation, various tools have been developed. One of the most common solutions is the use of a heart rate monitor. The advantage of this sensor is the quantification of heart rate during the session without the subjective inter-individual bias. However, this method of quantification has a poor correlation with the training load of muscle strengthening. This limitation has a strong impact on the estimation of adapted activity sessions due to the large proportion of exercises focused on the neuromuscular aspect. To address this issue, the analysis of human movement would be a complementary tool to estimate energy expenditure according to the different types of exercises proposed during the sessions. This analysis has been greatly facilitated with the arrival of deep learning for the classification of different movements according to the kinematics of the movement or actimetry. In this context two measurement systems stand out. On the one hand, the Actigraph is one of the most widely used tools in this field to quantify the training load according to the magnitude vector calculated by the accelerometer. This training load will be identified as low, moderate or high depending on the activities recorded by the sensor. On the other hand, the use of depth cameras to segment the human body is a rapidly evolving area. The data collected with this measurement system coupled with deep learning can classify a wide range of movements on several individuals at the same time. The use of these measurement systems would allow a better understanding of the estimation of the workload. Indeed, the association of the classification of exercises with the time of execution and the number of repetitions coupled with the heart rate would make it possible to have an accurate energy expenditure in ecological conditions. These data would allow for more precise individualisation of the management of elderly people for adapted physical activity sessions. This type of personalised care for frailty would be part of the future challenges of ageing well.
- Conditions
- Ageing
- Being tested
- Elderly
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ElderlyOther
A group of participants with physical activity (protocolized)
| Study group | Role | What they receive |
|---|---|---|
| Healthy participants aged more than 65 years old | Participation in 8 physical activity sessions, lasting 45 minutes, at the rate of 2 sessions per week Receives: Other: Elderly |
What is being measured
The primary outcome is the main question the study is designed to answer.
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 0
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 3
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 7
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 10
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 14.
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 17
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 21
Training Load
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Measured: Measured at day 24.
Secondary outcomes (2)
Exercises Intensity
Assessment of exercises intensity will be quantify by the Rate Perceived Exertion (RPE). The RPE scale ranges from 0 to 10. The number indicates how easy or difficult the participant finds an activity. For example, 2-3 is a light activity and 10 is a maximal effort activity.
Measured: Measured at day 0, day 3, day 7, day 10, day 14, day 17, day 21, day 24.
Exercises classification
To evaluate the prediction of the exercises, we will analyse the accuracy of the measurement with a confusion matrix on the prediction of the movements that decompose the different exercises. This matrix will allow us to determine the accuracy of the classifier according to the rate of false positives and the rate of false negatives.
accuracy = (TP + TN) / (TP + TN + FP + FN)
Where TP = number of True Positives, TN = number of True negatives, FP = number of False Positives, and FN = number of False Negatives.
Measured: Measured at day 0, day 3, day 7, day 10, day 14, day 17, day 21, day 24.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Feb 2023
- Study start5 Feb 2024
- Primary completion23 Jun 2025
- Study completion23 Jun 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for AgeingStudies of the same condition, open and under way.
- More trials run by Centre Hospitalier Universitaire de NiceThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 87 participants (actual)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Universitaire de Nice
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Olivier GUERIN, Principal investigator, University Hospital of Nice
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05740241
- Sponsor's protocol ID
- 22-AOI-03
- Acronym
- UNITS-APA
- Status last verified
- May 2026
- First submitted
- 25 Nov 2022
- Last updated
- 26 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 26 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Use of New Tools to Estimate the Intensity of Adapted Physical Activity Sessions
- ClinicalTrials.gov ID
- NCT05740241
- Acronym / sponsor ID
- UNITS-APA / 22-AOI-03
- Conditions
- Ageing
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 87 participants (actual)
- Lead sponsor
- Centre Hospitalier Universitaire de NiceUniversity, hospital or other
- Study start
- 5 Feb 2024 (actual)
- Primary completion
- 23 Jun 2025 (actual)
- Study completion
- 23 Jun 2025 (actual)
- First posted
- 22 Feb 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
In the field of sport/health, the prescription is generic and individualisation, which is still very rare, is generally linked only to physical performance. These limitations on the implementation of the sessions will result in limiting the effects of the training programme and increasing the risk of injury. It is therefore necessary to develop knowledge and tools to assist physicians and physical activity professionals in their decision making.
The aim of the study is to improve the precision of the calculation of the training load in order to better individualise the management of the participants.
Detailed description
Physical activity has been recommended for many years by various health authorities. Indeed, numerous studies have demonstrated the effects of physical activity on the quality of life, the gain of autonomy and the reduction of functional limitations in the elderly. This problem is becoming more and more present with the increase in life expectancy, which increases the prevalence of individuals reaching the status of elderly person. These forecasts suggest that more and more people will have to live with the consequences of age. From this point of view, the management of these people through adapted physical activity is necessary to relieve the health system by limiting the risks of frailty and thus hospitalisation among the elderly. In order to promote adapted physical activity, the role of specialists in this field is to set up physical activity sessions that solicit the neurocognitive, neuromuscular and cardiorespiratory aspects through balance, muscle strengthening and aerobic exercises. These sessions will be defined according to different criteria such as pathology, level of accomplishment of the exercises and the perceived difficulty of the session. For participants, the most common method of quantification is the Borg Rating of Perceived Exertion (RPE) scale. This measure consists of measuring the perception of effort on a scale ranging from 6 for "no perceived effort" to 20 for "maximum effort". The use of this tool has the advantage of having a strong correlation with heart rate at moderate intensities. These different parameters will allow the adapted physical activity engineer to determine a training load according to these different parameters. This training load will then allow the next session(s) to be adjusted to best suit the functional capacities of the participants and thus individualise the treatment of these people. However, this training load is subjective. For professionals in adapted physical activity, the quantification of the training load of the different sessions is based on personal experience. This method is difficult to quantify and generalise to other professionals. Similarly, the feeling of the difficulty of the session is specific to each participant. The quantification of the RPE will be strongly impacted by the last exercises of the session and the group effect. To address this limitation, various tools have been developed. One of the most common solutions is the use of a heart rate monitor. The advantage of this sensor is the quantification of heart rate during the session without the subjective inter-individual bias. However, this method of quantification has a poor correlation with the training load of muscle strengthening. This limitation has a strong impact on the estimation of adapted activity sessions due to the large proportion of exercises focused on the neuromuscular aspect. To address this issue, the analysis of human movement would be a complementary tool to estimate energy expenditure according to the different types of exercises proposed during the sessions. This analysis has been greatly facilitated with the arrival of deep learning for the classification of different movements according to the kinematics of the movement or actimetry. In this context two measurement systems stand out. On the one hand, the Actigraph is one of the most widely used tools in this field to quantify the training load according to the magnitude vector calculated by the accelerometer. This training load will be identified as low, moderate or high depending on the activities recorded by the sensor. On the other hand, the use of depth cameras to segment the human body is a rapidly evolving area. The data collected with this measurement system coupled with deep learning can classify a wide range of movements on several individuals at the same time. The use of these measurement systems would allow a better understanding of the estimation of the workload. Indeed, the association of the classification of exercises with the time of execution and the number of repetitions coupled with the heart rate would make it possible to have an accurate energy expenditure in ecological conditions. These data would allow for more precise individualisation of the management of elderly people for adapted physical activity sessions. This type of personalised care for frailty would be part of the future challenges of ageing well.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Healthy participants aged more than 65 years old | – | Other: ElderlyParticipation in 8 physical activity sessions, lasting 45 minutes, at the rate of 2 sessions per week |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Older adult
- Study population
- healthy volonteers
Key inclusion criteria (3 listed)
- Person having signed the non-opposition
- Person affiliated to the social security system.
- Male or female adult over 65 years of age.
Key exclusion criteria (2 listed)
- Person under protective measures (guardianship, curators, private, under court protection).
- Person suffering from a neurological problem affecting mobility (MMSE test < 24).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ElderlyA group of participants with physical activity (protocolized) | Other | Healthy participants aged more than 65 years old |
Primary outcome
Training Load
Time frame: Measured at day 0
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 3
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 7
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 10
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 14.
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 17
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 21
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
Training Load
Time frame: Measured at day 24.
The training load measured after each physical activity session measured with the different methods. The training load will be estimate with: the number of sets x the number of repetitions x the intensity of the exercise. The measure of the intensity of the exercises will be compute from vector magnitude from actimetry and motion capture. For the control method, the intensity of the exercise will be estimate by adapted physical activity engineers.
2 secondary outcomes
Exercises Intensity
Time frame: Measured at day 0, day 3, day 7, day 10, day 14, day 17, day 21, day 24.
Exercises classification
Time frame: Measured at day 0, day 3, day 7, day 10, day 14, day 17, day 21, day 24.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 May 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Olivier GUERIN principal investigator
University Hospital of Nice
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Ageing, run by Centre Hospitalier Universitaire de Nice at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Training Load (time frame: Measured at day 0). The study lists 8 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 May 2026.