Scores & Insights

Sahha analyzes device activity daily (per 24 hours) (data such as sleep, steps and more) to create the Sahha Mental Health Scores, Wellbeing Scores and other health insights for each end user. You can display or action within your application or access through the Sahha REST API .

Each call to the analyze method documented here returns each Sahha Health Scores

Consider exploring our design principles for best practices around displaying Sahha data.

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How to get scores from the last 24 hours

Get the most recent scores for the previous 24 hours in the user's local timezone. The default time period for an analysis is the previous 24 hours.

• iOS

• Android

• Flutter

• React Native

// Analyze Previous 24 Hours
// Leave date range empty

Sahha.analyze(includeSourceData: true) { error, json in
    if let error = error {
        print(error)
    } else if let json = json {
        print(json)
    }
}

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How to get scores by date range

You can provide an optional data range if you would like to receive multiple scores over a specific time period. The response will include an array of scores for each 24 hour segment in that time period.

• iOS

• Android

• Flutter

• React Native

// Analyze Previous 7 Days
// Add a date range

let today = Date()
let sevenDaysAgo = Calendar.current.date(byAdding: .day, value: -7, to: today) ?? Date()
Sahha.analyze(dates: (startDate: sevenDaysAgo, endDate: today)) { error, json in
    if let error = error {
        print(error)
    } else if let json = json {
        print(json)
    }
}

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200 Response

The response will be in JSON format. An example response includes these fields:

{
	"inferences": [
		{
			"id": "26051AB2-867F-4F8D-B134-0031C20D3FDC",
			"type": "stress",
			"state": "low",
			"score": 0.34,
			"factors": [
				{
					"name": "active_hours",
					"value": 0.017
				},
				{
					"name": "daily_steps",
					"value": 0.045
				},
				{
					"name": "activity_goals",
					"value": -0.002
				},
				{
					"name": "sedentary_periods",
					"value": -0.057
				},
				{
					"name": "activity_deviation",
					"value": 0.031
				}
			],
			"inputData": ["age", "sleep", "steps", "heart_rate"]
		},
		{
			"id": "601ADC2F-4830-45E7-B538-F7821EC009EA",
			"type": "depression",
			"state": "none ",
			"score": 0.14,
			"factors": [
				{
					"name": "active_hours",
					"value": 0.017
				},
				{
					"name": "daily_steps",
					"value": 0.045
				},
				{
					"name": "activity_goals",
					"value": -0.002
				},
				{
					"name": "sedentary_periods",
					"value": -0.007
				},
				{
					"name": "activity_deviation",
					"value": 0.001
				}
			],
			"inputData": ["age", "sleep", "steps"]
		},
		{
			"id": "601ADC2F-4830-45E7-B538-F7821EC009EA",
			"type": "anxiety",
			"state": "medium",
			"score": 0.62,
			"factors": [
				{
					"name": "active_hours",
					"value": 0.034
				},
				{
					"name": "daily_steps",
					"value": 0.015
				},
				{
					"name": "activity_goals",
					"value": -0.004
				},
				{
					"name": "sedentary_periods",
					"value": -0.007
				},
				{
					"name": "activity_deviation",
					"value": 0.02
				}
			],
			"inputData": ["age", "sleep", "steps", "screen"]
		},
		{
			"id": "acde070d-8c4c-4f0d-9d8a-162843c10333",
			"type": "sleep",
			"state": "high",
			"score": 0.75,
			"factors": [
				{
					"name": "active_hours",
					"value": 0.015
				},
				{
					"name": "daily_steps",
					"value": 0.085
				},
				{
					"name": "activity_goals",
					"value": -0.011
				},
				{
					"name": "sedentary_periods",
					"value": -0.007
				},
				{
					"name": "activity_deviation",
					"value": 0.021
				}
			],
			"inputData": ["age", "gender", "sleep", "activity"]
		}
	],
	"createdAt": "2023-07-31T12:00:35+12:00"
}

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204 Response

An empty but successful response.

// An analysis is not ready yet
// Try again in 24 hours
// Empty JSON
{}

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Data Sources

Data sources are required to generate an analysis.

Data Source	Description	Android	iOS
sleep	User sleep patterns	✓	✓
steps	User walking patterns	✓	✓
screen	User device screen time	✓	X
heart	User heart patterns	X	✓
blood	User blood patterns	X	✓
age	User age	✓	✓
gender	User gender	✓	✓

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Device Sensors

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Demographics

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